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INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCES Volume 1, No 5, 2011
© 2011 Anurag Ohri et al., licensee IPA- Open access - Distributed under Creative Commons Attribution License 2.0
Research article ISSN 0976 – 4402
Received on December, 2010 Published on January, 2011 772
Error Involved in Estimation of Site Sensitivity Index (SSI) for Land filling
of Municipal Solid Waste
Anurag Ohri.1 , P.K. Singh
2
1-Assistant Professor, Department of Civil Engineering, Institute of Technology,
Banaras Hindu University, Varanasi, India
2- Associate Professor, Department of Civil Engineering, Institute of Technology,
Banaras Hindu University, Varanasi, India
aohri.civ@itbhu.ac.in
doi:10.6088/ijessi.00105020007
ABSTRACT
An environmental Index known as Site Sensitivity Index (SSI) was developed by Central
Pollution Control Board (CPCB) in association with National Environmental Engineering
Research Institute (NEERI), India to quantify and compare the sensitivity of different
sanitary landfill sites on the basis of accessibility, receptor, environmental, socio-economic,
waste management practices, climatological and geological criteria. The SSI integrates
parametric effects of all attributes about suitability of site for landfilling and generates a
single number expressing the sensitivity of the site for municipal solid waste disposal. The
index is based on the impact of 32 attributes and their relative significance as assessed by a
group of experts. It therefore necessitates ascertaining all 32 attributes for the selected sites
and then compare their respective suitability based on SSI. In case, data related with any or a
few attribute(s) are not available, comparing and finalization of landfill site is not possible
using this approach. This paper attempts to estimate and report the error introduced in the
value of SSI due to unavailability of such required data. An attempt has been made to classify
attributes into high, medium and low weight categories based upon their significance in
finding the SSI. The SSIs have been calculated for two sites of Varanasi, one site of
Bangalore and one arbitrarily selected most sensitive site. The analysis of this study indicates
that the error may be high (>10%) if more than two data of high weight category are not
available, whereas a marginal error (5-10%) is incurred if up to 10 parameters having low or
middle weights are not available. A software program has been developed in Visual Basic to
calculate SSI based on available data and guide the user about the importance of the missing
attributes.
Keywords: Environmental Index, Site Sensitivity Index (SSI), Municipal Solid Waste
Disposal, Landfill site selection, Error Estimation.
1. Introduction
A large number of environmental indices have been developed in last four decades. Various
indices are developed to quantify the pollution or quality of water and air. Usually, the
indices are formulated based either on studies conducted by the indices developers or on the
Delphi technique (Kumar and Alappat, 2009). An approach involving the selection of
variables, formulation of the sub index functions, and their aggregation by the developers
themselves has been adopted for Horton‘s Water Quality Index (WQI) (Horton 1965), Prati‘s
Implicit Index of Pollution (Prati et al. 1971), Dinius WQI (Dinius 1972), and Walski and
Parker‘s Index (Walski and Parker 1974). However, the Delphi technique has been used for
developing the National Sanitation Foundation NSF WQI (Brown et al. 1970), Dalmatia WQI
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 773
(Gijanovic 1999), Water Quality Indexing System for Rivers and Streams (Smith 1990), and
Leachate Pollution Index (Kumar and Alappat, 2003).
Municipal solid waste management (MSWM) is one of the major environmental problems
throughout the world. Very few indices are developed so for to quantify the impacts of
different waste management activities. Kumar and Alappat (2003) developed a technique to
quantify the leachate contamination potential of sanitary landfills on a comparative scale in
terms of the leachate pollution index (LPI).
Landfill site selection is one of the important tasks for MSWM planners. Air, water and soil
pollution from the unscientifically selected disposal sites have been well known fact (Kumar
and Alappat, 2005). Central Pollution Control Board (CPCB) under the Ministry of
Environment and Forest (MoEF) with National Environmental Engineering Research
Institute (NEERI), Nagpur, India has developed a technique to quantify the suitability of site
for sanitary landfilling on a comparative scale in terms of the Site Sensitivity Index (SSI)
(CPCB, 2003). The SSI is an increasing scale index, wherein a lower value indicates that site
has less sensitivity to the impacts (preferable) and higher value indicates that site has high
sensitivity to the impacts (undesirable). The SSI has many possible applications including
ranking of potential landfill sites, prioritization of management plan initiatives and public
information. CPCB (2003) reported comparison and ranking of two potential municipal sites
at Kannahallo and Seegehalli in Banaglore based on SSI estimation following this approach,
Ohri and Singh (2009) attempted evaluation of two possible sites (Padaw and Karsada) in
Varanasi for landfill.
Kumar and Alappat (2005) considered estimation of errors involved in calculating Leachate
Pollution Index (LPI) due to non availability of data. The LPI is based on the concentration of
18 parameters, and the study reported the effect on LPI due to reducing number of available
parameters from 18 to 8. In case of landfill site selection, the SSI is an aggregated value
based on 32 attributes and their relative significance. Hence for calculating SSI, values of all
32 attributes are to be ascertained regardless of their high or low weight. It appears
reasonable therefore to assess the effect of non availability of some data on calculated value
of SSI in terms of error with respect to SSI estimated using all 32 attributes.
2. Methodology Adopted
2.1. Site Sensitivity Index (SSI)
CPCB (2003) has selected a set of 32 attributes for calculating an integrated index for ranking
of municipal solid waste disposal sites. The selected attributes are grouped into 7 categories
viz. accessibility, receptor, environmental, socio-economic, waste management practices,
climatological and geological. Sensitivity Index is a scale indicating degree of sensitivity of
individual attribute. This scale ranges from ‗0‘ (indicating low or very less potential hazard)
to ‗1‘ (indicating a high potential hazard). Thus, for each attribute a four level sensitivity
scale (0-0.25, 0.25-0.50, 0.50-0.75 and 0.75-1.00) has been considered. A numerical value
called weight has been assigned to each category, in accordance with the relative magnitude
of impact using a pair wise comparison technique. Within a category, the weight of each
attribute is assigned by following the same procedure of pair wise comparison. A total of
1000 point weights are assigned to all the 32 attributes grouped into 7 categories as shown in
Table 1.
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 774
Table1: Attributes and Calculation of Site Sensitivity Index for Landfilling (CPCB, 2003)
Sr.
No.
Attribute Weights 0.0-0.25 0.25-0.5 0.5-0.75 0.75-1.0
Accessibility Related ( No of Attributes 2, Total Weight 60)
1 Type of road 25 National
highway
State highway Local road No road
2 Distance from
collection area
35 < 10 km 10-20km 20-25km > 25km
Receptor Related (No of Attributes 8, Total Weight 250)
3 Population within
500 meters
50 0 to 100 100 to 250 250 to 1000 > 1000
4 Distance to nearest
drinking water
source
55 > 5000 m 2500 to
5000m
1000 to 2500
m
< 1000m
5 Use of site by nearby
residents
25 Not used Occasional Moderate Regular
6 Distance to nearest
building
15 > 3000 m 1500 to 3000
m
500 to 1500 m < 500m
7 Land use / Zoning 35 Completely
remote
(zoning not
applicable)
Agricultural Commercial
or industrial
Residential
8 Decrease in property
value with respect to
distance
15 > 500 m 2500 to
5000m
1000 to 2500
m
< 1000 m
9 Public utility facility
within 2 km
25 Commercial
and industrial
area
National
heritage
Hospital Air port
10 Public acceptability 30 Fully
accepted
Acceptance
with
suggestions
Acceptance
with major
changes
Non
acceptance
Environmental Related (No of Attributes 7, Total Weight 305)
11 Critical
environment
45 Not a critical
environment
Pristine
natural areas
Wetlands,
flood plains,
and preserved
areas
Major habitat
of endangered
or threatened
species
12 Distance to nearest
surface water
55 > 8000m 1500 to
8000m
500 to 1500m < 500 m
13. Depth to ground
water
65 > 30m 15 to 30m 5 to 15m < 5m
14 Contamination 35 Air, water or
food
contamination
Biota-
contamination
Soil
contamination
only
No
contamination
15 Water quality 40 Highly
polluted
Polluted Potable Confirming to
standard
16 Air quality 35 Highly
polluted
Polluted Confirming to
industrial
standards
Confirming to
residential
standards
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 775
17 Soil quality 30 Highly
contaminate
Contaminated Average No
contamination
Socio-economic Related (No of Attributes 4, Total Weight 110)
18 Health 40 No problem Moderate High Severe
19 Job opportunities 20 High Moderate Low Very low
20 Odour 30 No odour Moderate
odour
High odour Intensive foul
odour
21 Vision 20 Site not seen Site partly
seen (25%)
Site partly
seen (75%)
Site fully seen
Waste Management Practice Related (No of Attributes 2, Total Weight 85)
22 Waste quantity/ day 45 < 250 tons 250 to 1000
tons
1000 to 2000
tons
> 2000 tons
23 Life of site 40 > 20 years 10-20 years 2-10 years < 2 years
Climatological Related (No of Attributes 2, Total Weight 40)
24 Precipitation
effectiveness index*
25 < 31 31 to 63 63 to 127 >127
25 Climatic features
contributing to Air
pollution
15 No problem Moderate High Severe
Geological Related (No of Attributes 7, Total Weight 125)
26 Soil permeability 35 >1 x10-7
cm/sec
1x10-5
to
1x10-7
cm/sec
1x10-3
to
1x10-5
cm/sec.
< 1 x10-3
cm/sec.
27 Depth to bedrock 20 > 20m 10 to 20m 3 to 10 m < 3m
28 Susceptibility to
erosion and run-off
15 Not
susceptible
Potential Moderate Severe
29 Physical
characteristics of
rock
15 Massive Weathered Highly
weathered
30 Depth of soil layer 30 > 5 m 2-5m 1-2m < 1m
31 Slope pattern 15 < 1% 1-2% 2-5% >10%
32 Seismicity 20 Zone 1 Zone II Zone III Zone IV&V
*Precipitation effectiveness index is the ratio of annual precipitation to annual evaporation.
2.2 Variable aggregation
The weighted linear sum aggregation function has been used for the calculation of SSI and is
given by Equation 1:
1
n
i i
i
SSI w s
(1)
SSI= Total Score of Site Sensitivity Index
iw =Weight of ith
attribute; is = sensitivity of ith
attribute; n=no of attributes for calculating
SSI=32 ; and 10001
nwi
i
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 776
Based upon the actual measurement and the opinion of the experts, the aggregated SSI is
calculated for each site. Table 2 gives the decision criteria for landfill site selection based on
total score of SSI.
Table 2: Decision Criteria for a landfill site selection (CPCB, 2003)
Total Score of SSI Site Description
< 300 Less sensitive to the impacts (Preferable)
300 to 750 Moderate
> 750 Highly sensitive to the impacts (undesirable)
2.3. Errors involved in calculating site sensitivity index due to non-availability of data
When the data for any attribute included in SSI are not available, the normalized SSIm can be
calculated using the data set of the available attributes by using Equation 2:
1m
1
1
m
i i
i
m
i
i
nwi
i
w s
SSI X
w
(2)
where m number of attributes for which data are available, ( m<32)
and 1
m
i
i
w
<1000
The weights for the available attributes are normalized by proportionate redistribution so that
1
m
i
i
w
= 1000 and accordingly the SSI is calculated.
Error involved in calculated SSIm due to non availability of data can be calculated by using
Equation 3:
m100
SSI SSIError X
SSI
(3)
3. Case Study
To assess the errors involved due to non-availability of data in the estimated value of SSI,
case studies of two potential landfill sites of Varanasi (Padaw and Karsada), one of
Banagalore (Kannahallo) and one arbitrarily selected very sensitive site have been considered.
Based on judged attribute measurement (AM) for a site, the sensitivity index (SI) is assigned
with the help of Table 1 and the attribute score (AS) is calculated by multiplying SI with the
respective weight of that attribute. The SSI is the summation of all 32 attribute scores (ASs).
The results of such calculation of SSI for all sites are presented in table 3 and 4.
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 777
Table 3: SSI calculation for sites of Varanasi (Padaw and Karsada)
S.
No.
Attribute w Padaw Karsada
AM SI AS AM SI AS
1 Type of road 25 National Highway 0.15 3.75 Local Road 0.35 8.75
2 Distance from
collection point
35 9 km 0.25 8.75 14 km 0.4 14
3 Population within 500
meters
50 >1000 0.75 37.5 250-1000 0.6 30
4 Distance to nearest
drinking water source
55 400 m 0.9 49.5 1000m 0.75 41.25
5 Use of site by nearby
residents
25 Moderate 0.5 12.5 Occasional 0.25 7.5
6 Distance to nearest
building
15 <500 0.75 11.25 500-1500m 0.65 9.75
7 Land use/Zoning 35 Agricultural 0.50 17.5 Completely
remote
0 0
8 Decrease in property
value with respect to
distance
15 No decrease in
Property Value
0.1 1.5 No decrease in
Property Value
0.1 1.5
9 Public utility facility
within 2 kms
25 No public utility 0 0 No public utility 0 0
10 Public acceptability 30 Acceptance with
major changes
0.75 22.5 Acceptance with
suggestions
0.3 9
11 Critical environments 45 Flood Plain 0.5 22.5 Not a critical
environment
0.1 4.5
12 Distance to nearest
surface water
55 850 m 0.6 33 900m 0.60 33
13 Depth to ground water 65 8m 0.7 45.5 12m 0.6 39
14 Contamination 35 Soil
contamination
0.6 21 No
contamination
0.9 26.25
15 Water quality 40 Polluted 0.5 20 Potable 0.75 30
16 Air quality 35 Confirming to
industrial
standards
0.6 21 Confirming to
residential
standards
0.8 28
17 Soil quality 30 Contaminated 0.25 7.5 Average 0.6 18
18 Health 40 Moderate 0.35 14 No problem 0.15 6
19 Job opportunities 20 Low 0.5 10 Low 0.5 10
20 Odour 30 High Odour 0.6 18 Moderate 0.25 7.5
21 Vision 20 Site partly seen
(75%)
0.75 15 Site partly seen
(25%)
0.3 6
22 Waste quantity/day 45 250 to 1000
tonnes
0.35 15.75 250-1000 tonnes 0.35 15.75
23 Life of site 40 2-10 years 0.65 26 10-20years 0.35 14
24 Precipitation
effectiveness index
25 31 to 63 0.35 8.75 31-63 0.35 8.75
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 778
25 Climatic features
contributing to Air
pollution
15 No problem 0 0 No problem 0 0
26 Soil permeability 35 1x10-5to 1x10
-7 0.3 10.5 1x10
-5to 1x10
-7 0.3 10.5
27 Depth to bedrock 20 >20m 0.1 2 >20m 0.1 2
28 Susceptibility to
erosion & run-off
15 Moderate 0.7 10.50 Moderate 0.6 9.00
29 Physical
characteristics of rock
15 Massive 0.2 3 Massive 0.2 3
30 Depth of soil layer 30 >5 m 0.1 3 >5 m 0.1 3
31 Slope pattern 15 <1% 0.1 1.5 <1% 0.1 1.5
32 Seismicity 20 Zone III 0.5 10 Zone III 0.5 10
Total Score 483.25 407.50
w=Weight, AM=Attribute Measurement, SI=Sensitivity Index, AS=Attribute Score
Table 4: SSI calculation for the site at Bangalore and one arbitrary site (CPCB, 2003)
S.
No.
Attribute w Kannahallo Arbitrary High Sensitive Site
AM SI AS AM SI AS
1 Type of road 25 SH 0.35 8.75 No road 0.85 21.25
2 Distance from
collection point
35 25 km 0.75 26.25 26 km 0.75 26.25
3 Population within 500
meters
50 100 0.25 12.5 1000 0.75 37.5
4 Distance to nearest
drinking water source
55 200 m 1 55 200 m 1 55
5 Use of site by nearby
residents
25 Not Used 0 0 Occasional 0.25 6.25
6 Distance to nearest
building
15 100 1 15 100 1 15
7 Land use/Zoning 35 completely
Remote
0 0 Residential 0.8 28
8 Decrease in property
value with respect to
distance
15 No decrease in
Property Value
0 0 Decrease in
Property Value
0.7 10.5
9 Public utility facility
within 2 kms
25 No Public Utility 0 0 Hospital 0.75 18.75
10 Public acceptability 30 No complains 0.15 4.5 Non acceptance 0.75 22.5
11 Critical environments 45 Not a critical
environment
0.15 6.75 Preserved areas 0.85 38.25
12 Distance to nearest
surface water
55 1.5 km 0.5 27.5 300 m 0.8 44
13 Depth to ground water 65 5 m 0.75 48.75 2 m 1 65
14 Contamination 35 No contamination 1 35 No contamination 1 35
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 779
15 Water quality 40 Potable 0.75 30 Potable 1 40
16 Air quality 35 confirming to
residential
standards
1 35 confirming to
residential
standards
1 35
17 Soil quality 30 Average 0.75 22.5 Average 0.75 22.5
18 Health 40 Moderate 0.25 10 High 0.75 30
19 Job opportunities 20 Low 0.5 10 Very low 1 20
20 Odour 30 Moderate 0.35 10.5 Moderate 0.45 13.5
21 Vision 20 Site Partly Seen
(25%)
0.3 6 Site Partly Seen
(50%)
0.6 12
22 Waste quantity/day 45 1197 tonnes 0.6 27 1500 tonnes 0.8 36
23 Life of site 40 21 months 0.8 32 21 months 0.8 32
24 Precipitation
effectiveness index
25 31 to 63 0.5 12.5 31 to 63 0.5 12.5
25 Climatic features
contributing to Air
pollution
15 No problem 0 0 Moderate 0.5 7.5
26 Soil permeability 35 1X10-4
to 1X10-5
0.5 17.5 1X10-4
to 1X10-5
0.7 24.5
27 Depth to bedrock 20 10-40 m 0.3 6 18-20 m 0.5 10
28 Susceptibility to
erosion & run-off
15 Not susceptible 0 0 Potential 0.5 7.5
29 Physical characteristics
of rock
15 Weatherland 0.3 4.5 Weatherland 0.5 7.5
30 Depth of soil layer 30 0.3 to 3m 0.75 22.5 2 m 0.75 22.5
31 Slope pattern 15 2% 0.25 3.75 1% 0.25 3.75
32 Seismicity 20 Zone I 0 0 Zone II 0.5 10
Total Score 489.75 770.00
w=Weight, AM=Attribute Measurement, SI=Sensitivity Index, AS=Attribute Score
It is observed that based on SSI scores, both the potential sites of Varanasi as well as the
Kannahallo site of Bangalore fall in moderate impact ( 300< SSI score<750) category. The
unknown high sensitivity site, as expected achieves a SSI score of 770 (greater than 750).
To study the effect of non availability of data on estimated SSI, the whole range of attributes
were judiciously classified into three categories: Low, Middle and High, based on their
weight ranges as given in Table 5.
A software program has been developed in Visual Basic to calculate SSI based on available
data. This program is a part of our programe on development of Environmental Decision
Support System for Municipal Solid Waste Management (EDSS-MSWM) and discussed
elsewhere (Ohri and Singh, 2010). For studying the effect of non availability of data, the SSI
for each site is calculated by dropping one attribute from a category and the error introduced
in calculated SSIm (with respect to the SSI using all 32 attributes) is estimated. The procedure
is repeated by successively ignoring additional attributes of this weight category and
estimating the resultant error in calculated SSIm. Fig. 1 shows the snapshot of the program
for calculating SSI/SSIm along with number of missing data and % error due to non
availability of such data. The EDSS-MSWM also guides the user about the importance of the
missing attributes.
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 780
Table 5: Classification of attributes based on weight
Attributes No. of
Attributes
Weight
ranges
Weight
Category
Critical environments, Waste quantity/day, Population
within 500 meters, Distance to nearest drinking water
source, Distance to nearest surface water, Depth to
ground water
6 65 to 45 High
Public acceptability, Soil quality, Odour, Depth of soil
layer, Distance from collection point, Land use/Zoning,
Contamination, Air quality, Soil permeability, Water
quality, Health, Life of site
12 40 to 30 Middle
Distance to nearest building, Decrease in property value
with respect to distance, Climatic features contributing to
Air pollution, Susceptibility to erosion & run-off,
Physical characteristics of rock, Slope pattern, Job
opportunities, Vision, Depth to bedrock, Seismicity, Type
of road, Use of site by nearby residents, Public utility
facility within 2 kms, Precipitation effectiveness index
14 25 to 15 Low
Figure 1: Snapshot of developed software program for calculating SSI, report on suitability
of site and error due to missing data, if any.
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 781
3.1. Effect of non availability of attributes with high weight factors
If the data of ―depth to ground water‖ (Table 1, S. No. 13, weight= 65) is presumed to be
unknown, SSIm (m=31) is calculated using Eq.2. The percentage error in calculated SSIm is
estimated using Eq. 3. Subsequently, the next attribute (Distance to nearest drinking water
source, S. No. 4, weight= 55) is also presumed to be unknown. The SSIm (m=30) is similarly
calculated using Eq.2, and the percentage error in SSIm (m=30) with respect to SSI (n=32) is
estimated. The procedure is repeated till only 26 attributes data are assumed to be available
and all 6 low weight data are missing. The results of such analysis is shown in Fig. 2.
From Fig. 2 it is observed that when attributes of high weight are not available, the error is
negative indicating that the calculated SSIm is less than actual SSI, thereby projecting the site
to be less sensitive to impacts than actual. The percentage error varies from -2.08 (m=31) to a
maximum of -16.33 (m=28). The error exceeds 10%, if more than one attribute of high
weight category is missing.
Figure 2: Variation of percentage error in SSI with decreasing number of attributes due to
non availability of high weight parameters
Table 6: Estimating errors involved in calculated site sensitivity index due to non availability
of high weight attributes
Attribute wi AM SI (pi) AS
(n=32)
wi pi
AS
(n=30)
wi pi
AS
(n=28)
wi pi
AS
(n=26)
wi pi
Depth to ground water 65 8m 0.7 45.5 - - -
Distance to nearest
drinking water source
55 400 m 0.9 49.5 - - -
Distance to nearest surface
water
55 850 m 0.6 33 33 - -
Population within 500
meters
50 >1000 0.75 37.5 37.5 - -
Critical environments 45 Flood Plain 0.5 22.5 22.5 22.5 -
Waste quantity/day 45 250 to 1000
tonnes
0.35 15.75 15.75 15.75 -
Water quality 40 Polluted 0.5 20 20 20 20
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 782
Health 40 Moderate 0.35 14 14 14 14
Life of site 40 2-10 years 0.65 26 26 26 26
Distance from collection
point
35 9 km 0.25 8.75 8.75 8.75 8.75
Land use/Zoning 35 Agricultural 0.5 17.5 17.5 17.5 17.5
Contamination 35 Soil
contamination
0.6 21 21 21 21
Air quality 35 Confirming to
industrial
standards
0.6 21 21 21 21
Soil permeability 35 1x10-5to
1x10-7
0.3 10.5 10.5 10.5 10.5
Public acceptability 30 Acceptance
with major
changes
0.75 22.5 22.5 22.5 22.5
Soil quality 30 Contaminated 0.25 7.5 7.5 7.5 7.5
Odour 30 High Odour 0.6 18 18 18 18
Depth of soil layer 30 >5 m 0.1 3 3 3 3
Type of road 25 National
Highway
0.15 3.75 3.75 3.75 3.75
Use of site by nearby
residents
25 Moderate 0.5 12.5 12.5 12.5 12.5
Public utility facility
within 2 kms
25 No public
utility
0 0 0 0 0
Precipitation effectiveness
index
25 31 to 63 0.35 8.75 8.75 8.75 8.75
Job opportunities 20 Low 0.5 10 10 10 10
Vision 20 Site partly
seen (75%)
0.75 15 15 15 15
Depth to bedrock 20 >20 0.1 2 2 2 2
Seismicity 20 Zone III 0.5 10 10 10 10
Distance to nearest
building
15 <500 0.75 11.25 11.25 11.25 11.25
Decrease in property value
with respect to distance
15 >5000 0.1 1.5 1.5 1.5 1.5
Climatic features
contributing to Air
pollution
15 No problem 0 0 0 0 0
Susceptibility to erosion &
run-off
15 Moderate 0.7 10.5 10.5 10.5 10.5
Physical characteristics of
rock
15 Massive 0.2 3 3 3 3
Slope pattern 15 <1% 0.1 1.5 1.5 1.5 1.5
Summation 1000 483.25 388.25 317.75 279.5
Total weight 1000 880 775 685
Normalized SSIm 483.25 441.19 410.00 408.03
Percentage error 0 -8.7 -15.16 -15.57
w=weight, AM=Attribute Measurement, SI=Sensitivity Index, AS=Attribute Score
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 783
3.2. Effect of non availability of attributes with low weight factors
When a similar procedure is followed by removing attributes with low weights, starting with
―slope pattern‖ (S. No. 31, weight= 15) and % error in calculated SSIm (m<32) with respect to
SSI (m=32) is plotted with remaining number of attributes, the results are obtained as shown
in Fig 3.
From Fig. 3 it is observed that percentage error may increase from 0.75 to 17.58% when
attributes having low weights are ignored one by one up to 14. A positive % error in SSI
indicates a high calculated SSI with respect to the actual SSI for the site, suggesting that the
site is being projected more sensitive than really it is. The error is within 10% when up to 10
attributes having low weights are considered non available.
Figure 3: Variation of percentage error in SSI with decreasing number of attributes due to
non availability of a few low weight parameters
3.3 Effect of non availability of attributes with middle weight factors
Following a similar procedure for middle weight attributes, starting with ―Public
Acceptability‖ (S. No. 10, weight= 30) and estimating the error in calculated SSIm (m<32)
with respect to SSI (m=32), a plot of % error with remaining number of attributes is obtained
as shown in Fig 4.
From Fig. 4, it is observed that when middle weights attributes are not available, the error
may be positive (indicating a site to be more sensitive than actual) as well as negative
(meaning a site is indicated less sensitive than actual). The maximum positive error is 7.46%
with all twelve middle weight parameter missing whereas the maximum negative error is
-6.07% with nine attributes non available.
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 784
Figure 4: Variation of percentage error in SSI with decreasing number of attributes due to
non availability of middle weight parameters
4. Discussion
It is observed that the percentage error are positive and the estimated SSIm (m<32) are higher
than the actual SSI (m=32) when data for the attributes with low weights are missing. Thus
the site is reported as more sensitive to impacts than actually it is. This may give some factor
of safety for the considered site in terms of sensitivity. On the contrary, the percentage error
are negative and the estimated SSIm are lower than the actual SSI in case of high weights
attributes being non available, indicating a false sense of security on a vulnerable site. A
marginal positive error up to 10% is introduced in calculated SSI if ten attributes of low
weight category are considered not available. This means the actual SSI for a site can
reasonably be assessed using only 22 available attributes. Basically there are fourteen low
weight attributes in SSI calculation, out of which 10 (receptor related 2, climatological
related 1, Socio-economic related 2, and geological related 5) have weights in 15-20 range.
The weight of these 10 attributes is 170, which gets redistributed while normalizing the SSIm.
In case of high weight attributes, the error in calculated SSI exceeds 10% just with the non
availability of two attributes, and the error being negative a high sensitive site may be
reported less sensitive. Non availability of middle weight attributes may introduce either
positive or negative error in SSI, but remains within 10% with up to 10 attributes being not
available.
5. Conclusions
Site Sensitivity Index (SSI) calculated on the basis of 32 attributes as suggested by CPCB
(2003) serves as a useful basis for ranking the suitability of landfill site. In case of constraints
of time and resources, or non availability of data related with some attributes, a marginal
error up to 10% is introduced in calculated SSI if upto 10 attributes of low or middle weight
are missing. The high weight attributes must be available for SSI calculations in order to
reasonably assess the suitability of the site for landfill. Hence a classification of attributes in
high, medium and low categories appear desirable in order to prioritize the efforts for data
collection. A software program has been developed to calculate SSI, report on the suitability
of site for landfill, and number of missing data, if any, along with percentage error introduced
in calculated SSI due to such missing data.
Error Involved in Estimation of Site Sensitivity Index (SSI) for Landfilling of Municipal Solid Waste
Anurag Ohri, P.K.Singh
International Journal of Environmental Sciences Volume 1 No.5, 2011 785
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