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. 628 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 630 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 633 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 References Aczel, J., Saaty, T., 1983. Procedure for synthesizing ratio judgments. Journal of Mathematical Psychology 27, 93–102. Awad, A.R., Obeidat, M., Al-Shareef, M., 2004. Mathematical-statistical models of generated hazardous hospital solid waste. Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances and Environmental Engineering 39 (2), 315–327. Karamouz, M., Zahraie, B., Kerachian, R., 2003. Development of a master plan for water pollution control using MCDM techniques: a case study. Journal of Water International 28 (4), 478–490. Karamouz, M., 2003. Identification and Classification of the Hospital Wastes in the Province of Khuzestan, Iran. 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