Waste Management 27 (2007) 626–638
www.elsevier.com/locate/wasman
Developing a master plan for hospital solid waste management:
A case study
Mohammad Karamouz a, Banafsheh Zahraie a, Reza Kerachian
Nemat Jaafarzadeh b, Najmeh Mahjouri c
a,*
,
a
School of Civil Engineering, University of Tehran, Tehran, Iran
Faculty of Health Science, University of Ahvaz, Ahvaz, Iran
School of Environmental Engineering, University of Tehran, Tehran, Iran
b
c
Accepted 13 March 2006
Available online 27 June 2006
Abstract
Disposal of about 1750 tons of solid wastes per day is the result of a rapid population growth in the province of Khuzestan in the
south west of Iran. Most of these wastes, especially hospital solid wastes which have contributed to the pollution of the environment
in the study area, are not properly managed considering environmental standards and regulations. In this paper, the framework of a
master plan for managing hospital solid wastes is proposed considering different criteria which are usually used for evaluating the pollution of hospital solid waste loads. The effectiveness of the management schemes is also evaluated. In order to rank the hospitals and
determine the share of each hospital in the total hospital solid waste pollution load, a multiple criteria decision making technique, namely
analytical hierarchy process (AHP), is used. A set of projects are proposed for solid waste pollution control and reduction in the proposed framework. It is partially applied for hospital solid waste management in the province of Khuzestan, Iran. The results have shown
that the hospitals located near the capital city of the province, Ahvaz, produce more than 43% of the total hospital solid waste pollution
load of the province. The results have also shown the importance of improving management techniques rather than building new facilities. The proposed methodology is used to formulate a master plan for hospital solid waste management.
2006 Elsevier Ltd. All rights reserved.
1. Introduction
With rapid population growth and industrialization, disposal of hospital solid wastes, which include a wide range
of infectious hazardous wastes pollutants, has become
one of the main environmental issues. A limited number
of studies related to the hospital solid waste management
have been made, especially for the development of management schemes for hospital wastes.
Liberti et al. (1996) proposed a model to provide an
optimal solution to the overall waste management system
involving characterization, handling (collection, storage,
*
Corresponding author. Tel.: +98 21 61112176; fax: +98 21 66403808.
E-mail addresses: karamouz@ut.ac.ir (M. Karamouz), bzahraie@ut.
ac.ir (B. Zahraie), kerachian@ut.ac.ir (R. Kerachian), n_jaafarzadeh@
yahoo.com (N. Jaafarzaheh), mahjouri@ut.ac.ir (N. Mahjouri).
0956-053X/$ - see front matter 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.wasman.2006.03.018
transportation), and incineration of hospital wastes produced by a large sanitary district.
Awad et al. (2004) carried out statistical analyses to
develop models for predicting the quantity of waste generated at two public and private hospitals in Jordan. In their
models, number of patients, beds, and hospitals were identified as significant factors on quantity of waste generated.
Multiple regression was also used to estimate the quantities
of wastes generated.
Morrissey and Browne (2004) reviewed different types of
models that are currently being used in the area of municipal, hospital, and industrial waste management and highlighted some major shortcomings of these models. Based
on their work, most of the models identified in the literature are decision support models that are divided into three
categories based on: cost–benefit analysis, life cycle assessment, and multi-criteria decision making. They showed
M. Karamouz et al. / Waste Management 27 (2007) 626–638
627
Nomenclature
k
kmax
A
aij
cij
CRIn
II
IIh
IR
Eigen value of pair-wise comparison matrix
dominant eigenvalue
pair-wise comparison matrix
elements of pair-wise comparison matrix
value of criterion i for alternative j
inconsistency index for randomly filled matrixes
with dimension n
inconsistency index
inconsistency index for basic criteria
inconsistency ratio
that the shortcomings of the current waste management
models include concerns regarding the refinements of the
evaluation steps rather than addressing the decision making process.
Karamouz et al. (2003) proposed a framework for developing a master plan for water resources pollution control
using Multiple Criteria Decision Making (MCDM) techniques. They proposed an integrated set of direct, indirect
and supporting water pollution control projects. Source
reduction, demand management, capacity expansion,
human resources development, development of monitoring
and sampling network, research and technology transfer,
institutional changes, and improvement of legal framework
have been the major initiatives recommended in the master
plan.
A new framework to develop a master plan for hospital
solid waste management is introduced in this paper. Different criteria can be used for evaluating the pollution of existing hospital solid waste loads and the effectiveness of the
management schemes. In order to rank the hospitals and
determine the share of each hospital in the total hospital
solid waste pollution load, a multiple criteria decision making technique, namely analytical hierarchy process (AHP), is
used. In this framework a comprehensive set of direct, indirect, and supporting projects are proposed for hospital solid
waste pollution control. The proposed methodology is evaluated using data from 40 hospitals in the province of Khuzestan. In this province, most of the hospital solid wastes are
stored, disposed or burnt in open spaces. In some cases,
these solid wastes (including infectious wastes) are disposed
in landfills used for the disposal of domestic wastes, which
can cause considerable environmental and health problems.
The proposed framework includes the following steps:
m1, . . . , mn index of sub-criteria
N
number of decision-makers
rij
elements of row iand column j in the dimensionless decision matrix
w
Eigen vector of pair-wise comparison matrix
wai
weight of alternative i
Wi
weight of alternative i
wai
relative weight of alternative i
wI MAX the maximum weight of the intervals related to
the corresponding criterion
Determination of the spatial and temporal variations of
the hospital solid waste pollution loads (pollution load
zoning).
Ranking of the pollution sources and determining the
share of each hospital in the environmental pollution
through solid waste disposal.
Development of a GIS-based data bank and a Management Information System (MIS).
Proposing a set of direct, indirect, and supporting projects considering the relative share of hospitals.
Evaluation of the proposed projects in pollution control
in the study area.
Development of a timetable for project implementation.
Determination of the needed budget on an annual basis.
The flowchart of the activities required for developing a
hospital solid waste pollution control master plan is presented in Fig. 1.
2. Analytical hierarchy process (AHP)
The AHP method was first developed by Saaty (1980
and 1994) and has been widely used in both fields of theory
and practice. This method is based on the pair-wise comparison of the importance of different criteria and sub-criteria. The consistency of comparisons should also be
verified. The difference between the dominant eigenvalue
of the pair-wise comparison matrix, kmax, and the matrix
dimension, k, is used by Saaty (1980 and 1994) in defining
the inconsistency Index, II:
II ¼
kmax k
:
k1
ð1Þ
The inconsistency ratio, IR, is then defined as:
Data gathering.
Identification of system components and the interactions among them.
Analysis of economic and social consequences of the
hospital solid waste pollution.
Selection of a comprehensive set of indicators, which
shows different aspects of the hospital solid waste pollution load and management.
IR ¼ II=CRI;
ð2Þ
where, CRI is the Inconsistency Index of the random matrix
obtained by calculating II for randomly filled matrix. If
IR < 10%, then the consistency criterion is satisfied; otherwise the decision maker should be asked to revisit the
pair-wise comparisons. This procedure continues until all
pair-wise comparisons satisfy the consistency criterion.
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M. Karamouz et al. / Waste Management 27 (2007) 626–638
Major Steps
Identification of systems components and interactions among them
Development of a GIS-based data bank and a MIS
Analysis of economic, social, and political consequences of the solid waste pollution
Selection of a comprehensive set of indicators, which show different aspects of hospital
solid waste pollution load and solid waste management.
Determination of the spatial and temporal variations of the solid waste pollution loads
First Phase: Problem Identification
Data gathering using questionnaires or by reviewing reports
Ranking the pollution sources and determining the share of each medical unit in
environmental pollution through solid waste disposal
Evaluation of the effectiveness of the proposed
projects in pollution control in the study area
Environmental impacts of current
and ongoing projects
Budget associated with each proposed project
Socio-economic impacts of the
proposed projects
Priority of implementation of the projects
Time table for budget spending
Framework of cooperation among
sectors and public
Monitoring and Evaluation
Second Phase: Master Plan Development
and Action Items
Proposing a set of direct and supporting projects
considering the relative share of hospitals in
environmental pollution through solid waste disposal
Time table of action items
Development of monitoring and
evaluation system
Adjustments considering
changing needs
Third Phase:
Monitoring and
Evaluation
Flexible Planning Approaches
Fig. 1. Major phases for development of a master plan for hospital solid waste pollution control.
The eigenvector of pair-wise comparison matrix is used
for estimating the relative weight (importance or priority)
of different alternatives. For this purpose, the following
relation is used:
!
mi
X
Xn
a
wi ¼
wj
½ci;k wj;k
ð3Þ
j¼1
k¼1
a
i
wai
W ¼ Pm
a
j¼1 wj
;
ð4Þ
where, wai is the weight of alternative (sector) i; wj the relative
weight of basic criterion j which is the jth element of eigen-
vector for pair-wise comparison matrix of basic criteria; ci,k
the value of sub-criterion k for alternative i divided by the
maximum value of that sub-criterion for all alternatives;
wj,k the relative weight of sub-criterion k of basic criterion
j; W ai the relative weight of alternative i; m/n the total number of alternatives/basic criteria and mi is the number of subcriteria defined for basic criteria i. The selected criteria and
sub-criteria for this study are shown in Fig. 2. Different hospitals are considered as alternatives. The relative weight of
alternative i, ðW ai Þ, which is calculated based on the proposed method, can show the share of the hospital i in contaminating the environment through solid waste disposal.
M. Karamouz et al. / Waste Management 27 (2007) 626–638
Level 1
Level 2
Level 3
629
Level 4
Separation (0.25)
Storage (0.15)
Hazardous
Solid
Wastes
(0.65)
Solid waste
management
(0.35)
Solid waste
generation
(0.65)
Disposal (0.45)
Separation (0.3)
Storage (0.15)
Nonhazardous
Solid
Wastes
(0.35)
Objective:
Determination of the
share of each hospital
in total hospital solid
waste pollution
Transportation (0.15)
Hazardous
Solid
Wastes
(0.75)
Transportation (0.15)
Disposal (0.4)
Pharmaceutical
Wastes (0.25)
Sharps (0.3)
Human tissues (0.45)
Semi-domestic (0.2)
Paper (0.1)
Nonhazardous
Solid
Wastes
(0.25)
Food wastes (03)
Miscellaneous (0.4)
Fig. 2. Proposed hierarchy structure of indicators and their relative weights (numbers in the parentheses) for ranking of hospitals based on their solid
waste generation and management.
3. Case study
The proposed methodology is applied for classification
and ranking of the hospitals located in the Khuzestan province of Iran. About 40 hospitals are considered in the
study. The total hospital solid waste generated in the study
area is about 13 tons per day, of which about 27% is hazardous wastes (Karamouz, 2003).
In this study, by revising an existing questionnaire provided by the Department of Environment (DOE) in Iran,
a more comprehensive questionnaire was designed for
gathering the basic data related to the main characteristics
of hospital solid wastes and their disposal in the study
area. The main criteria proposed for the hospital solid
waste classification, as stated in the American Resource
Conservation Recovery Act (RCRA) and Australian
guidelines for waste management in the health industry
(NHMRC, 1999) are considered in developing the new
questionnaire. The questionnaires were completed by evaluating the qualitative and quantitative characteristics of
the solid wastes, as well as the processes utilized for separation, packing, transportation, incineration, and disposal
of the hazardous and non-hazardous wastes in each hospital. Some additional data such as the number of beds, the
amount of disposed waste and wastewater, and the meth-
ods of treatment or disposal were also gathered. This
information includes the composition of the hospital solid
wastes such as the relative weights of the semi-domestic,
non-hazardous, infectious, paper, food, and other types
of solid waste materials in each hospital, as well as in
the province.
Different steps in developing the master plan for hospital
solid waste management were listed in the previous section.
Some of the main steps are explained as follows:
Data gathering: Detailed data and information which
are required for evaluating each hospital should be gathered by visiting the medical unit, sending questionnaires
and reviewing related reports. Data deficiencies may be
tackled via engineering judgment and using experts’
opinion.
Identification of the pollution sources: Identification of
the biomedical pollution sources is the first step in developing of a master plan. Different criteria such as hospital solid waste quantity and quality can be used for
classification of these pollution sources.
Determination of the evaluation criteria: A comprehensive set of indicators should be selected for evaluating
the pollution load, environmental impacts, and solid
waste management in each hospital. Indicators can be
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M. Karamouz et al. / Waste Management 27 (2007) 626–638
classified to two main criteria, namely solid waste generation and management. For these criteria, some sub-criteria related to the separation, storage, packing, transfer
and disposal of the different types of hospital wastes can
be defined.
Determination of the share of each hospital in environmental pollution through solid waste disposal: Ranking
of hospitals based on a hierarchy structure of indicators
is important for identifying the main pollution sources.
The proposed hierarchy structure of indicators presented in Fig. 2 can be used for this purpose.
improve the effectiveness of the direct projects, are usually
proposed as the indirect and support projects, respectively.
The supporting projects are proposed considering the following general themes:
The related weight of the criteria and sub-criteria in each
level should be determined using a pair-wise comparison.
As stated by Pomerol and Barba-Romero (2000), the idea
of introducing pair-wise comparisons between different criteria is to make pair-wise comparisons at a time rather than
assigning weights to the whole set of criteria. In order to
incorporate engineering judgment, a group decision-making method developed by Aczel and Saaty (1983) has been
used. In this method, each element in group pair-wise comparison matrix is assumed to be equal to the geometric
mean of corresponding elements in different pair-wise comparison matrixes of decision makers.
The analytical hierarchy process (AHP), which is
described in the following section, can be used for ranking
the hospitals, as well as determining their relative share of
solid waste pollution.
4. Results of applying the AHP method for ranking of
hospitals
Development of a GIS-based data bank and MIS: The
collected data is stored in a bank with statistical analysis and report generation capabilities. The GIS-based
maps of the study area are for evaluating the spatial
and temporal variations of the solid waste pollution
loads. They include pollution loads and solid waste
characteristics.
Proposing solid waste pollution control projects: The
major projects of the master plan are selected and
ranked based on how effective they are in reducing the
environmental pollution through hospital solid waste
disposal. The projects are usually proposed by managers
and experts of different hospitals located in the study
area, and then they are prioritized considering their
impacts on the overall master plan. Finally, the most
effective projects are selected in three classes namely
the direct projects, the indirect projects, and the supporting projects. The direct projects, which can directly
reduce the solid waste disposal pollution load, can be
categorized in the following categories:
– Source reduction.
– Solid waste recycling and reuse.
– Solid waste treatment.
– Solid waste incineration and disposal considering
environmental issues.
Other projects that have an indirect impact on solid
waste pollution control, as well as the projects aimed to
Integrated sampling and monitoring network.
Research and technology transfer.
Human resources capacity building and improvement of
legal framework.
Monitoring and evaluation.
A hierarchy structure of indicators is proposed (Fig. 2)
for ranking the hospitals based on their solid waste generation and the management techniques. As shown in Fig. 2,
there are two main criteria for evaluating the solid waste
generation and management in the second level of the structure, which are evaluated based on the characteristics of the
hazardous and non-hazardous hospital solid wastes. In this
structure, some sub-criteria such as separation, storage,
transportation and disposal of different types of hospital
solid wastes are used, which are related to the solid waste
management criterion in level 2 in the hierarchy structure
of the criteria. Solid waste generation is qualified by evaluating the amount of hazardous and non-hazardous hospital
wastes. Hazardous hospital wastes include pharmaceutical
wastes, sharps, and human and animal tissues. The relative
weights of the criteria are calculated based on pair-wise
comparisons set by the decision-makers and experts familiar
with the system. These comparisons are usually presented in
the form of pair-wise comparison matrices. Decision-makers can assign a consistent weight when only two criteria
are involved; however when there are several criteria, the
weighting and judgments about their importance in environmental polluting through solid waste disposal are rather
difficult and could result in inconsistent assessments. In this
study, a group of decision makers and experts, including six
environmental and system engineers who were experts in
hospital waste management and analytical hierarchy process, set the pair wise comparison matrices. The geometric
mean method (Saaty, 1994) is used to find the group judgment about the relative importance of sub-indicators, which
resulted in the weights shown in Fig. 2.
The following matrix shows the group judgments for the
sub-criteria of the non-hazardous solid wastes as an example:
631
M. Karamouz et al. / Waste Management 27 (2007) 626–638
Table 1
Classification of the daily weight of disposed hospital solid wastes in the province of Khuzestan, Iran (tons/year)
Class number
Type of hospital solid waste
Semi-domestic
1
2
3
4
5
6
7
8
9
0.1–20
20–44
44–60
60–72
72–90
90–140
140–210
210–365
365–751
Paper
0.1–1
1–4
4–6
6–8
8–10
10–14
14–18
18–27
27–53
Food wastes
0.1–9
9–19
19–34
34–59
59–79
79–114
114–200
200–319
319–453
Miscellaneous
Infectious
0.1–4.5
4.5–8.5
8.5–11
11–13.5
13.5–15.5
15.5–19
19–29
29–50
50–56
As it can be seen in this matrix, the group judgments are
inconsistent. For example, the relative importance of
separation compared with storage is equal to two and the
relative importance of storage compared with transportation is equal to one. If the decision-maker comparisons
were consistent, the relative importance of separation
compared with transportation would be 2 · 1 = 2 but the
decision maker indicated 1.5. In this study, the inconsistency of pair-wise comparison matrices are quantified using
the inconsistency index (IIb), which is equal to 0.01 for the
above matrix. It is less than 0.1, so it is considered
consistent.
As the number of alternatives (hospitals) is more than 9,
application of ordinary AHP method will be limited as suggested by Saaty (1990). Therefore, the value of the indicators located in the third level of the hierarchy structure is
clustered into nine classes considering their range of variations. Table 1 presents the characteristics of the selected
classes for ranking the hospitals located in the Province
of Khuzestan. For different types of hospital wastes, the
range of weight of solid wastes that are annually generated
in different hospitals is divided into nine classes so that the
numbers of hospitals located within different classes are
almost the same. For each class, an indicator value is
selected, which is the average weight of solid wastes of hospitals located in the class (Table 2). The total score (grade)
of each hospital is calculated by summation of a partial
Pharmaceutical wastes
Human tissues
Sharps
0.1–3.5
3.5–9
9–20
20–29
29–36
36–49
49–86
86–147
147–160
0.1–1.1
1.1–3.1
3.1–5.6
5.6–7.1
7.1–9.5
9.5–14.5
14.5–18.5
18.5–27
27–33
0.1–3.9
3.9–9.5
9.5–14.5
14.5–20
20–29
29–43
43–45
45–75
75–102
grade (PG) related to each criterion located in the last level
of hierarchy structure. PG is calculated as follows:
PG ¼
wInd wI
;
wI MAX
ð5Þ
where wI is the weight of the interval I that the evaluator
score falls into; wInd the weight of the indicator in the last level (Fig. 2), which is the relative importance of the indicator
compared to the others and wI MAX is the maximum weight of
the intervals related to the corresponding criterion.
The relative weight of each hospital (its share in environmental pollution through solid waste disposal) is calculated
for each alternative (hospital) by the summation of partial
grades of the indicators located in the last level and the
final ranking is obtained.
The overall inconsistency index ðIIÞ is estimated by combining the inconsistency index of basic criteria and the
effects of sub-criteria as follows:
IIe
IIb
II ¼ IIa þ ½ 0:35 0:65
þ ½ 0:65 0:35
IIf
IIc
IIg
þ ½ 0:75 0:25
;
ð6Þ
IIh
where, IIa is the inconsistency index of the pair-wise
comparison matrix of the basic criteria located in level
1; IIb, IIc are the inconsistency indices of the pair-wise
Table 2
Selected indicator values for each class of the annual weight of disposed hospital solid wastes in the province of Khuzestan, Iran (tons/year)
Class number
1
2
3
4
5
6
7
8
9
Type of hospital solid waste
Semi-domestic
Paper
Food wastes
Miscellaneous
9.17
33.5
52.4
68.14
81.5
133.3
166.58
303.5
572
2.33
5.2
7.5
9.75
12
16.2
20.14
21
46.5
3.5
12.4
22.5
42.8
63.33
90.9
131.83
224.75
386
1.67
5.25
9.75
12.2
14.82
16.75
21.71
34
53.78
Infectious
Pharmaceutical wastes
Human tissues
Sharps
1.5
5.4
15.5
24.5
31.25
39.8
53.4
92.08
149
0.75
2.4
4.82
6.5
7.9
11.1
16
20.3
29.2
0.92
5.2
11.91
15.88
23.5
32.9
44
55.4
100
632
M. Karamouz et al. / Waste Management 27 (2007) 626–638
comparison matrices of the indicators located in level 2,
which are related to the Solid Waste Generation and
Solid Waste Management criterion, respectively; and
IIe, IIf, IIg, IIh are the inconsistency indices of the
pair-wise comparison matrices of the indicators located
in level 3.
The overall random inconsistency index of the hierarchy
structure CRI is then estimated similar to II, but in Eq. (6),
IIi, which is the inconsistency index of matrix i, is replaced
with CRIn. CRIn is the inconsistency index of a n · n random matrix and n is the dimension of the pair wise comparison matrix (Saaty, 1990). Therefore, CRI can be calculated
as:
CRI2
CRI4
CRI ¼ CRI2 þ ½ 0:35 0:65
þ ½ 0:65 0:35
CRI2
CRI4
0
CRI3
¼ 0 þ ½ 0:35 0:65
þ ½ 0:75 0:25
0
CRI4
0:58
0:9
¼ 1:56
þ ½ 0:75 0:25
þ ½ 0:65 0:35
0:9
0:9
ð7Þ
The overall Inconsistency Ratio is then estimated using Eq.
(2) as 0.04, which is less than 10%. Therefore, the group
judgments in matrices are used for estimating the share
of different hospitals in pollution of the system due to waste
disposal.
Tables 3 and 4 present the shares of contamination for
different zones as well as the top 10 most polluting hospitals, which are estimated using Eqs. (3) and (4). As shown
in Table 3, Ahvaz region produces the highest load of hospital solid waste disposal. The share of this region in polluting the environment is more than 50%. Table 5 presents the
share of all investigated hospitals considering different relative weights for solid waste generation and management.
As presented in this table, the share of each hospital in polluting the environment is not considerably dependent on
the relative weights of the criteria. Therefore, the calculated
values can be properly used in developing the master plan.
Ranking of hospitals may depend on the selected set of criteria. For example, Table 6 presents shares of the 10 most
polluting hospitals in generating infectious wastes, which
are partially different with the 10 most polluting hospitals
based on hierarchy structure of criteria presented in Fig. 2.
Table 3
Share of hospitals located in different regions in the province of Khuzestan (Iran) in polluting the environment through solid waste disposal (%)
Rank
Region (city)
Hospital Beds
Inpatient and out-patient dischargesa
Share (%)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Ahvaz
Behbahan
Abadan
Dezful
Masjedsoleiman
Khorramshahr
Ramhormoz
Shoosh
Eazeh
Mahshahr
Shooshtar
Sousangerd
Andimeshk
Omidieh
Shadgan
Aghajaary
3151
208
424
542
N/A
224
174
157
150
270
134
126
100
N/A
N/A
50
42,74,535
N/A
49,216
N/A
N/A
N/A
270,000
5502
N/A
N/A
10,311
N/A
72,000
988,420
44,200
33,725
53.8
6.7
5.4
4.1
3.8
3.4
3.2
2.9
2.5
2.4
2.3
2.2
2.2
2
1.6
1.5
a
Aproximate numbers.
Table 4
Share of 10 most polluting hospitals in the province of Khuzestan (Iran) in polluting the environment through solid waste disposal (%)
Rank
Hospital code
Hospital beds
Inpatient and out-patient discharges
Region (city)
Share (%)
1
2
3
4
5
6
7
8
9
10
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
500
350
401
225
224
50
164
174
182
130
N/A
14,354
166,216
83,493
N/A
N/A
288,740
270,000
13,518
6000
Ahvaz
Ahvaz
Ahvaz
Ahvaz
Khoramshahr
Behbahan
Ahvaz
Ramhormoz
Abadan
Ahvaz
6
4.6
4
3.8
3.4
3.3
3.2
3.2
2.9
2.8
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M. Karamouz et al. / Waste Management 27 (2007) 626–638
Table 5
Share of hospitals in polluting the environment considering different weights for
main criteria of solid waste generation and management
Hospital
code
WSM: 0.2,
WSP: 0.8
WSM: 0.28,
WSP: 0.72
WSM: 0.35,
WSP: 0.65
WSM: 0.43,
WSP: 0.64
WSM 0.5,
WSP: 0.5
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12
H13
H14
H15
H16
H17
H18
H19
H20
H21
H22
H23
H24
H25
H26
H27
H28
H29
H30
H31
H32
H33
H34
H35
H36
H37
H38
H39
H40
7.3
5.6
4.6
4.4
3.6
3.8
3.5
3.3
2.7
2.9
2.7
2.8
2.4
2.8
2.3
2.6
2.8
2.1
2.5
2.3
1.8
2.2
2.3
2.1
2.2
2.1
2.5
1.9
2
1.5
1.7
1.7
1.4
1.1
1
1.2
1.3
1.2
1.1
1
6.6
5
4.3
4.1
3.5
3.5
3.3
3.2
2.8
2.8
2.7
2.7
2.6
2.8
2.4
2.6
2.7
2.3
2.5
2.4
2.1
2.3
2.3
2.1
2.2
2.2
2.3
2
2.1
1.7
1.7
1.7
1.6
1.4
1.3
1.4
1.4
1.2
1.2
1.1
6
4.6
4
3.8
3.4
3.3
3.2
3.2
2.9
2.8
2.8
2.7
2.7
2.7
2.6
2.6
2.6
2.5
2.5
2.4
2.3
2.3
2.3
2.2
2.2
2.2
2.2
2.1
2.1
2
1.8
1.7
1.7
1.6
1.5
1.5
1.4
1.2
1.2
1.2
5.4
4.2
3.8
3.6
3.4
3
3
3.1
3
2.8
2.8
2.6
2.8
2.7
2.7
2.6
2.4
2.7
2.4
2.5
2.5
2.3
2.4
2.2
2.3
2.3
2.1
2.2
2.1
2.2
1.8
1.7
1.9
1.8
1.7
1.6
1.5
1.3
1.3
1.3
5
3.9
3.6
3.4
3.3
2.8
2.9
3.1
3.1
2.6
2.8
2.6
2.8
2.7
2.8
2.7
2.4
2.8
2.4
2.5
2.7
2.4
2.4
2.2
2.3
2.3
2
2.3
2.1
2.4
1.9
1.7
2
2
1.8
1.8
1.6
1.3
1.3
1.3
jects of the master plan are selected and ranked based on
how effective they are in reducing the environmental
impacts through solid waste disposal in the study area.
The projects are initially proposed by the managers and
experts of different hospitals; then they are prioritized considering their impacts toward the objective of this study.
Finally, the most effective projects are selected as follows:
Equipping all hospitals in the study area with solid
waste collection, separation, and packing systems based
on the DOE standards and the guidelines proposed in
this master plan.
Providing hospitals with transportation of the hospital
solid wastes.
Disposing the domestic and semi-domestic solid wastes
generated in the hospitals in municipal landfills.
Expanding the existing hospital waste management
capacities.
Developing guidelines for solid waste management in
emergency conditions.
Developing comprehensive MIS for hospital solid waste
generation and management in the study area.
Proposing and implementing the research projects
related to the hospital solid waste recycling.
Developing local regulations and guidelines for hospital
solid waste collection, separation, storage, transportation, and disposal considering the existing national
regulations.
Optimally locating incinerators and hospital waste treatment facilities.
Capacity building and human resources for solid waste
recycling in hospitals.
Training the staff for solid waste management systems in
different hospitals.
WSM: weight of solid waste management.
WSP: weight of solid waste production.
Table 7
Comparing the generated hospital wastes and the capacity of incinerators
in the Khuzestan province, Iran
Table 6
Share of 10 most polluting hospitals in the province of Khuzestan (Iran) in
generating infectious wastes (%)
Rank
1
2
3
4
5
6
7
8
Hospital
code
Share in
total
infectious
waste
generation
H6
H5
H8
H31 H17 H27 H9 H10 H19 H31
5.86 2.49 2.13 2.02 1.85 1.74 1.6 1.6
9
City
Generated Special wastes
waste(kg/h) which should
be incinerated
(kg/h)
Capacity of
the needed
incinerators
(kg/h)a
Abadan
Aghajary
Omidieh
Andimeshk
Ahvaz
Eizeh
Behbahan
Khoramshahr
Dezful
Ramhormoz
Sousangerd
Shadgan
Shoosh
Shooshtar
Mahshahr
Masjedsoleiman
Sum
39.71
0.54
8.79
0.00
168.71
21.13
17.00
20.83
43.75
10.42
13.71
0.75
12.50
4.50
9.75
14.88
386.97
49
0
28
0
713
65
53
33
12
22
22
0
22
13
5
23
1060
10
1.24 1.17
5. Outline of the master plan for hospital solid waste
management in the Khuzestan province
The main objective of this plan is to comply with the
regulations developed by the DOE during a 2-year time
horizon in processes such as hospital solid waste separation, storage, transportation, and disposal. The major pro-
a
9.37
0.08
5.42
0
105.42
6.25
10.12
6.25
2.3
4.17
2.08
0.08
4.17
2.21
0.8
4.46
163.2
Capacity of
the existing
incinerators
(kg/h)
350
150
–
150
1900
150
600
300
400
250
150
200
150
250
350
50
5400
The on-line time for each incinerator should be less than 5 h/day.
634
Table 8
Proposed methods and their priorities for storage, transportation, treatment and disposal of hospital solid waste in the province of Khuzestan, Iran
Type of
wastes
Waste management processes
Storage
Transportation
Indoor
Outdoor
Waste volume reduction
Indoor
Waste disinfection techniques
Outdoor
Interior
Waste disposal
Exterior
Waste Steriliza- Incine- Radia- Chemical Incinera- Steriliza- Land Incinera- Recycling
Packs and Special Cans Open Comp- Hand Hydraulic Pneumatic Shouting Waste Incinera- Comp- Paper
tion
filling tion and
ression recycling grinding tion
ration tion
disinfec- tion
cans ressing lorries machines instruments system carrying tion
cans for packs for
ash
tion
trucks
machines
sharp
infectious
disposal
objects
wastes
–
–
–
1
1
1
1
–
–
–
–
–
2
2
1
–
1
1
2
1
2
2
2
2
1
–
2
1
4
–
–
–
3
1
3
–
1
1
1
1
3
3
2
1
1
1
1
2
2
2
–
–
3
4
–
3
–
–
–
2
–
–
–
1
–
–
–
3
–
–
–
4
–
–
–
1
–
–
–
2
2
3
1
2
3
2
2
1
1
1
–
–
–
1
–
1
–
1
2
–
–
1
2
1
–
–
1
4
2
3
2
1
2
2
–
–
–
–
1
1
–
–
–
1
1
2
2
1
1
–
–
–
–
1
1
2
–
1
–
–
–
–
–
1
1
4
–
2
2
3
3
2
–
1
1
2
1
3
–
1
–
1. First priority; 2. Second priority; 3. Third priority.
Table 9
Proposed methods for disinfecting and disposing hospital solid waste in the study area
Hospital type
Disinfection and volume reduction methods
First priority
Second priority
Third priority
In emergency conditions
First priority
Second priority
Third priority
Clinics
Disinfection
–
Disinfection
Disinfection
–
Disinfection by autoclave
Small clinics
Disinfection by
autoclave
Incinerator
–
Disinfection by autoclave
Transferring to
incinerators
Landfilling
without grinding
Landfilling
without grinding
Landfilling
without grinding
Grinding and
landfilling
Incinerator
Transferring to
incinerators
Disinfection and
grinding
autoclave
to the
Landfilling of ash
Grinding and
landfilling
Incinerator
Disinfection and
grinding
–
Disinfecting by
or transporting
other hospitals
Disinfecting by
or transporting
other hospitals
Disinfecting by
or transporting
other hospitals
Grinding and
landfilling
Grinding and
landfilling
Grinding and
landfilling
Landfilling of ash
–
Medical laboratories
Transferring to the
incinerators
Transferring to the
incinerators
Transferring to the
incinerators
Disinfection and
grinding
autoclave
to the
Landfilling of ash
Grinding and
landfilling
Hospitals with less
than 50 beds (in all
cities except Ahvaz)
Hospitals with less than
50 beds (in Ahvaz)
Hospitals with less
than 200 beds
Disposal methods
autoclave
to the
–
–
Landfilling of
disinfected waste
(without grinding)
Landfilling of
disinfected waste
(without grinding)
Landfilling of
disinfected waste
(without grinding)
M. Karamouz et al. / Waste Management 27 (2007) 626–638
Semi-domestic
Paper
Food wastes
Infectious
wastes
Pharmaceutical
wastes
Sharps
Toxic and
carcinogenic
wastes
M. Karamouz et al. / Waste Management 27 (2007) 626–638
Fig. 3. The main menu of Khuzestan hospital solid waste Management Information System.
Fig. 4. The main data retrieval menu in Farsi for each hospital and the English translation.
635
636
M. Karamouz et al. / Waste Management 27 (2007) 626–638
Fig. 5. The main menu of data and information report generation.
Fig. 6. The menu of data and information report generation based on the location of the hospitals.
M. Karamouz et al. / Waste Management 27 (2007) 626–638
Monitoring and evaluation of the solid waste management systems in the hospitals.
The proposed AHP-based model is also used for
assessing the effectiveness of the above projects. The effectiveness of the proposed projects is evaluated using the
hierarchical structure of the criteria and their relative
weights, as calculated in this study (Fig. 2). In proposing
the pollution control projects, the existing capacities
should be considered. As an example, Table 7 provides
a comparison between the generated hospital wastes
and the capacity of incinerators in the Khuzestan province. As can be seen in this table, in most of the cities,
the total existing capacity of the incinerators is usually
much more than required capacity. It should also be
noted that the existing incinerators are in suitable condition. Therefore, the main problem of hospital solid waste
management in the study area is due to improper solid
waste storage, packing and transportation rather than
lack of facilities. Tables 8 and 9 present the proposed
methods for storage, transportation, treatment, and disposal of the hospital solid wastes in the study area.
The capital budget needed for improving the environmental problems of hospital solid wastes by implementing
direct/indirect and supporting projects are estimated as 340
million Iranian Rials (42,000 US Dollars) and 490 million
Iranian Rials (61,000 US Dollars), respectively. The
monthly operating cost for direct/indirect and supporting
projects are 417 million Iranian Rials (51,000 US Dollars)
and 437 million Iranian Rials (53,000 US Dollars), respectively. Most of the required capital budget should be
expended during the first year after implementing the master plan.
As mentioned before, the collected data should be
stored in a data bank with the capabilities of statistical
analysis and generating management reports. In this
study, a data bank and GIS-based maps of the study area
have been developed. The main menu of this system is
shown in Fig. 3. The main cities are shown in the right
hand side of the map. By selecting each city, the main
related hospitals are shown in the province map. By clicking on each hospital, some information related to the
selected hospital such as solid waste quantity and quality,
solid waste separation, storage, transportation, and disposal are presented (Fig. 4). In order to generate reports,
a menu has been developed (Fig. 5). In this menu, generating reports can be based on different characteristics of
the hospitals. For example, Fig. 6 shows the menu of
generating reports based on the location of the hospital.
The reports include all data that has been stored in the
data bank.
6. Summary and conclusion
Different aspects of developing a master plan for hospital solid waste pollution reduction are discussed in this
paper. Definition of objectives, identification of system
637
components and action items, and identification of a set
of proposed waste reduction projects are considered and
described in the context of a case study for Khuzestan
Province in Iran.
In order to estimate the effects of different hospitals on
the environmental pollution in the study area, a multi-criteria decision making (MCDM) technique, namely the
AHP method, is used. Subjective information about relative importance of different criteria is also incorporated
in this analysis. The consistency in engineering judgments
were also assessed and considered in finding the relative
importance of different waste indicators by utilizing the
AHP method.
Besides the proposed AHP based method, an economic
analysis is also introduced in order to consider the cost
associated with the environmental impacts of the pollution
load of different hospitals. It also shows how cost effective
the waste pollution control projects are. Since the economic-based methods, especially in the developing countries, suffer from data deficiencies and uncertainties
associated with inflation and high interest rates, the proposed MCDM method can be helpful because it is not
too data intensive and can combine the limited data,
experts’ opinions, and engineering judgments in defining
the criteria and their relative weights.
In this paper, the main objective of developing a master
plan framework has been to comply with the existing regulations and standards in a 2-year time horizon. The major
projects proposed in the master plan are pollution load
reduction, development of hospital solid waste separation,
storage, transportation and disposal systems, human
resources development, development of monitoring, treatment and sampling networks, research and technology
transfer, institutional changes and improvement of the
legal framework.
The breakdown of the total percentage of waste pollution generated through the activities of different hospitals,
the cost associated with different projects, and the estimated rate of pollution reduction by different projects have
also been determined.
The results show that the main problem of hospital solid
waste management in the province of Khuzestan is due to
improper solid waste storage, packing and transportation
rather than absence of facilities. The results of application
of the proposed framework in the province of Khuzestan
show that this methodology can be effectively used for
development of a master plan for hospital solid waste pollution control.
Acknowledgements
This study was partially supported by the Khuzestan
Department of Environment. Contributions of managers
and engineers of this department, especially Mr. Sepehrfar,
Mr. Lahijanzadeh, and Ms. Kaabi, as well as the contribution of research staff: Ashrafi, Saba, Karimi, Zolfagharpour, Saberi, and Ghobadi are hereby acknowledged.
638
M. Karamouz et al. / Waste Management 27 (2007) 626–638
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