1 Introduction

Nowadays, population growth, along with increasing municipal solid waste (MSW) production, plays a remarkable role in environmental pollution. MSW management, to recognize suitable landfill sites, is an indispensable step of environmental planning, where the selection of a landfill site for disposal of solid waste can assure habitat conservation and promote human health [1]. More importantly, environmental challenges caused by the leakage from MSW, which can potentially contaminate groundwater and surface water resources, are one of the significant and tangible environmental impacts of a landfill site, where appropriate ecological and socioeconomic circumstances, as well as precise engineering design of landfill site, will contribute greatly to reducing leakage and protection of the environment [2]. Selection of optimal landfill sites for MSW is one of the most important principles of urban planning which can be defined as a practical method to attain sustainable urban development. To reduce its environmental impacts, locating a landfill is the basis for sound management of MSW [3]. Regarding the negative environmental impacts of waste disposal on human health and welfare, environmental experts must decide on planning for MSW landfill based on the environmental capacity of land in cooperation with relevant public agencies [4]. Often, environmental negative consequences of landfill site selection are of interest to environmental specialists and related experts; proper site selection of MSW landfill through multi-criteria decision-making (MCDM) method within the framework of ecological capacity assessment can lead to establishing a logical framework. Parameters such as slope, geological formations, soil texture, proximity to surface water, groundwater depth, land use (forest, pastures, farmlands), proximity to population centers, proximity to protected areas, distance from industrial areas, distance from power transmission lines, and distance from access roads all play an pivotal role in selection of MSW landfill [5]. Some of the mentioned parameters have more importance to locating suitable landfills than other parameters, including groundwater depth, proximity to surface water sources, soil texture, type of geological formations, distance from protected areas, and distance from population centers [6]. Geographical information system (GIS) is a useful and high-performance tool in studies pertaining to sanitary landfill site selection, as a spatial decision support system (SDSS) with a strong set of tools to enter, store, display, analyze and model spatial data as well as the ability to handle large volumes of spatial data from different sources [7]. The potential advantage of using GIS for site selection lies within the fact that using GIS not only reduces time and saves money for MSW landfill site selection, but also provides a digital database for long-term monitoring of a landfill [8].

In addition to GIS, MCDM method can be applied to solve landfill site selection problems [9]. MCDM is based on the assumption that decision-making issues should be divided into smaller comprehensible sections that can be analyzed independently, and at the end, those decision-making segments will be integrated in a logical manner [9]. Integrating GIS and MCDM generates a strong problem-solving tool for spatial issues regarding the selection of MSW landfill [10]. This is because GIS analyzes spatial and descriptive criteria at the same time and turns raw data into valuable information, while MCDM, in turn, addresses ranking and prioritizing of landfill sites by considering ecological parameters [11]. Several studies have been carried out on landfill site selection for MSW in the context of multi-criteria evaluation (MCE) approaches. Osra and Kajjumba [12] applied an integration approach based on GIS and analytical hierarchy process (AHP) to demonstrate pragmatically the connections between the diverse landfill site selection factors in Makkah, Saudi Arabia. They found that this method would be an efficient method to identify the most desirable locations in Makkah [12]. Yildirim and Guler [13] used AHP, GIS, and weighted overlay method (WOM) based on weighted linear combination (WLC) for identification and selection of municipal solid waste disposal sites (MSWDSs) for the Mersin Region in the southeast of Turkey. They classified the suitability map indicating six suitability classes [13]. Torabi Kaveh et al. [14] utilized GIS-based multi-criteria evaluation (MCE) based on the AHP in terms of identifying the appropriate sites for the landfill in the Iranshahr Region. They obtained four suitability classes within the study area were identified [14]. Karimzadeh Motlagh and Sayadi [15] utilized MCDM methods based on WLC and ordered weighted averaging (OWA) and analytical network process (ANP) for the landfill site selection of the Birjand plain. Their research outcomes revealed that the OWA method, in comparison with WLC and ANP, had great potential and flexibility in the modeling of the complex decision-making problems [15]. Abd-El Monsef [16] used GIS, remote sensing, and AHP to identify and locate suitable locations for new landfill sites along coastal desert regions of the Red Sea in Egypt. They found two suitable sites for MSW landfill [16]. Ghobadi et al. [17] undertook an MSW landfill site selection, in Hamedan Province, by integrating GIS and AHP, and they classified areas based on three suitability classes [17]. In the present study, comparison of Fuzzy logic, based on WLC, and Boolean logic, in the ArcGIS 10.3 software environment, was made to select MSW landfill site in SaharKhiz Region in Gilan Province, according to the ecological and socioeconomic parameters.

2 Study area

The study area, SaharKhiz Region, is a part of the coastal zone of the Caspian Sea which is located in Gilan Province. SaharKhiz Region has a latitude of 37°19′N and a longitude of 50°13′E, which is placed 23 to 26 m below sea level. The region’s area is 1627.10 km2, and the slope of the land surface is toward the northwest. According to the field observation, the area has a few steep slopes and is mainly used for agriculture [18]. From surface water resources’ point of view, there are 11 permanent rivers and 2 permanent lakes in the area, among which Sefidrood and Shamrood are the most important permanent rivers in the area. SaharKhiz Region includes cities such as Roodsar, Langerood, Lahidjan, Astaneh Ashrafie, and Kia Shahr. Consequently, the study area has a high population density. On the other hand, the important protected habitats in the area, which are rich in flora and fauna, are Boojagh National Park, Amir Kolayeh Wildlife Refuge, Safrabashte Forest Reserve, and some other valuable wetlands. Also, dangerous facilities such as gas pipelines, Kelachay Mine, and Lahidjan Car Factory are located within the studied area [18]. Figure 1 shows the location of SaharKhiz Region in Gilan Province, Iran.

Fig. 1
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Location of SaharKhiz Region in Gilan Province, Iran

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3 Methodology

3.1 Boolean logic

To select the MSW landfill site in SaharKhiz Region, a large number of socioeconomic and ecological parameters are involved. After determining the ecological and socioeconomic sub-criteria in the GIS environment, a common projection coordinate system was determined for all of the layers based on the WGS 84/UTM zone 39 N. Then, by using the Boolean logic method, the constraint criteria reflect the imposed conditions regarding decision-making options. Constraints make it possible to consider the separated spatial options from the rest of the choices; in fact, the constraints contain the criteria in which there is no feasibility for the MSW site selection and should be considered as the separated criteria, including the slopes of more than 15%, areas situated inside floodplains, areas located at a distance of less than 100 m from active faults, areas placed in a distance of less than 1000 m from population centers, etc. [19]. Table 1 shows the layers and standards for landfill site selection regarding Iran’s Department of Environment (IDOE) requirement.

Table 1 Criteria and standards for the selection of landfill site by using Boolean logic [19]
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3.2 The Fuzzy logic approach based on WLC

The second method which is used in this research is the Fuzzy logic approach based on WLC, one of the most popular MCDM methods, in which standardization of spatial criteria is continuous. At first, standardization of criteria raster layers was used depending on the function type (whether ascending or descending). Since the importance of landfill spatial criteria varies, it is necessary to determine the weights of criteria using AHP before implementing the WLC method. In the following stage, questionnaires on the priority and importance of ecological and socioeconomic criteria were distributed among environmental experts [20]. One of the most common methods of spatial decision making based on GIS is applying AHP for weighting the criteria and sub-criteria. In order to determine the weight of ecological and socioeconomic criteria and sub-criteria, a pairwise comparison matrix of each element within every level was constructed. This matrix showed the importance of each element against another [17]. Next, experienced environmental experts’ comments were used to determine the priorities of every two criteria undergoing pairwise comparison. Finally, the geometric mean of their survey was used as an input to the expert choice (EC) software to determine the final weight of the ecological and socioeconomic sub-criteria [17]. While the AHP process determines the weight of indicator criteria, the rate of inconsistency can be calculated, so experts will be able to make a decision about pairwise judgments. If the rate of judgment inconsistency is equal to or smaller than 10% (0.1), it will be considered acceptable; otherwise, weighting should be repeated [21]. Table 2 shows the preference values for pairwise comparison of criteria and sub-criteria [22].

Table 2 The preferences values for pairwise comparison [22]
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Following this, each standardized factor was multiplied by the final weight obtained from AHP, and then layers were added together. The final map related to the calculated preference 0–1 is related to the suitable areas. This method is based on Eq. (1) [23], where S represents site suitability of the area, Wi is the final weight of the criteria, Xi is the Fuzzy value of the criteria, and n represents the number of criteria [24].

$$S = \sum\limits_{i = 1}^{n} {w_{i} x_{i} }$$
(1)

To integrate the WLC method into the spatial analysis, after preparing the raster maps of the ecological and socioeconomic parameters, a suitable approach for multi-criteria comparison of all the parameters needs to be considered, which is called MCE. In fact, due to the adverse essence of the ecological and socioeconomic parameters, all of the parameters should be chosen in a standard unit, in terms of being compared with each other. WLC method is one of the most fundamental approaches for standardization of data layers between the standard unit of zero and one, based on the standardization formulations for ascending and descending according to the type of data layer [25]. Table 3 shows the threshold values and Fuzzy membership function to standardize of different layers in Fuzzy logic for landfill site selection regarding IDEO requirements. Figure 2 presents several stages of MSW landfill site selection by comparing Boolean logic and Fuzzy logic based on WLC in the studied area.

Table 3 Threshold values and Fuzzy membership function to standardize the different layers in Fuzzy logic for landfill site selection [19]
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Fig. 2
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Stages of MSW landfill site selection by comparing Boolean logic and Fuzzy logic based on WLC in SaharKhiz Region in Gilan Province

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4 Site Selection Criteria

Generally, selecting a suitable landfill site would minimize the risk to human health as well as decrease the negative effects on the environment. Additionally, it will reduce the costs of waste disposal [26]. The selected areas for landfilling should be close to the source of waste and far from protected areas (wildlife refuges, national parks, natural monument, in addition to protected areas of Iran Department of Environment). Underground water depth in the area must be low, and access to the roads and transport routes should be facile. The area must be flat without any steep slope and far from surface water resources (rivers and lakes) or areas which are prone to earthquakes and faults. In fact, these areas have more capability for landfill site selection than others [27]. Table 4 shows the list and description of ecological criteria for MSW landfill site selection in SaharKhiz Region, Gilan Province. Table 5 shows the list and description of socioeconomic criteria for MSW landfill site selection in SaharKhiz Region, Gilan Province. To utilize the Fuzzy logic based on WLC, in terms of Iran’s Department of Environment (IDOE), all parameters related to ecological and socioeconomic parameters were standardized between the standard unit of zero and one [28]. Parameters include slope, flood, distance from the fault, distance from protected areas, distance from wetlands, distance from lakes, distance from the coast, distance from population centers, distance from power lines, distance from the gas pipeline, and distance from roads.

Table 4 List and description of ecological criteria for landfill site selection [29,30,31,32,33]
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Table 5 List and description of socioeconomic criteria for landfill site selection [29,30,31,32,33]
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5 Results

By using Iran’s Department of Environment (IDOE) regulation for MSW landfill site selection together with environmental experts’ views, which were utilized for ecological and socioeconomic sub-criteria, this study illustrated that ecological sub-criteria such as groundwater depth, distance from surface water resources, and flooding play a key role in landfill site selection. Also, among socioeconomic sub-criteria, distance from population centers (urban and rural) is an important factor for landfill site selection. As a result, if landfill site selection is done correctly and in accordance with environmental assessment (ecological and socioeconomic capacity), the urban environment will be protected, socioeconomic requirements will be met, and it will be in accordance with principles of sustainable development. After final map preparation using Boolean logic, it is shown that about 14.72% (239.53 km2) of SaharKhiz Region in Gilan Province has site suitability, whereas 85.28% (1387.57 km2) has unsuitable properties for landfill site selection. Also, in the final map prepared through Fuzzy logic based on WLC, it was determined that about 2.94% of SaharKhiz Region with an area of 47.83 km2 has very low site suitability; 17.31% of the region with an area of 281.73 km2 has low site suitability; 35.23% of the region with an area of 573.20 km2 has moderate site suitability; 28.65% of the region with an area of 466.23 km2 enjoys high site suitability; and 15.77% of the region with an area of 256.65 km2 is endowed with very high site suitability for MSW landfill site selection. In this study, standardization of ecological and socioeconomic sub-criteria on a continuous scale (between 0 and 1) is provided by employing Fuzzy logic, and as a result, the relative desirability of suitable areas for MSW landfill can be determined. Furthermore, the capacity of Fuzzy logic based on WLC in terms of allocating different relative weights to any of the ecological and socioeconomic sub-criteria in the process of information layer integration is one of the advantages of this method. Therefore, one can decide on MSW landfill site selection in SaharKhiz Region according to the region’s environmental capacity (region’s ecological and socioeconomic capacity).

As shown in Fig. 3, the local desirability range for MSW landfill site selection is discrete. Figure 3 represents MSW landfill site selection by applying Boolean logic in SaharKhiz Region of Gilan Province. In Fig. 4, site suitability for MSW landfill site selection in SaharKhiz Region is continuous. According to the ecological and socioeconomic parameters, unsuitable sites are scored zero and others are marked between zero and one. One of the most important differences among maps of Boolean logic and Fuzzy logic approach can be mentioned as being discrete and continuous structures, respectively. Figure 3 shows the final map resulted from Boolean logic, and Fig. 4 shows result from Fuzzy standardization of ecological and socioeconomic sub-criteria for MSW landfill site selection in SaharKhiz Region. Table 6 presents final weights and priorities assigned to the ecological and socioeconomic factors using the AHP method for MSW landfill site selection. In this study, the rate of inconsistency was calculated to be 0.05 in the Expert Choice software environment for ecological and socioeconomic parameters; therefore, judgment consistency was acceptable and weighting was conducted correctly by experts. Table 7 presents the result of different classes for landfill site selection using Boolean logic. Table 8 shows the result of different classes for landfill site selection using Fuzzy logic based on WLC.

Fig. 3
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Final map resulted from Boolean logic

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Fig. 4
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Final map resulted from Fuzzy logic based on WLC

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Table 6 Final weights and priorities assigned to the ecological and socioeconomic factors using AHP method
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Table 7 The result of different classes for landfill site selection using Boolean logic
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Table 8 The result of different classes for landfill site selection using Fuzzy logic based on WLC
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6 Conclusions

In this study, Boolean logic and Fuzzy logic approaches based on WLC were used to select MSW landfill sites in accordance with IDOE regulations. If the ecological and socioeconomic parameters of SaharKhiz Region, such as distance from areas with soil liquefaction, land ownership, future land use, groundwater vulnerability, and meteorological factors, such as rainfall, are used to determine landfill suitability and assessment, results will have high accuracy. In this study, comparison of Boolean logic and Fuzzy logic approaches, based on WLC, was employed to locate MSW landfill sites. Fuzzy logic allows standardization of ecological and socioeconomic sub-criteria in a continuous structure, and due to the wide range of suitability classification (between zero and one), experts’ ability for the selection of the most appropriate place for MSW plays a more important role than the Boolean logic. In fact, results from landfill site selection, using this method, have more compatibility with the environmental capacity of SaharKhiz Region (ecological and socioeconomic capacity). Given the ecological sensitivity of the aquifers in the north of Iran, it is recommended that in future research, both the soil textures types and geological formations permeability should be taken into account for MSW landfill site selection. To increase the accuracy of assessment, 1:10,000 scale maps should be produced. This study also recommends taking into account the rules and regulations of the Environmental Protection Agency (EPA) for MSW landfill site selection. In order to provide more accurate results based on ecological and socioeconomic parameters, it is suggested that the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method be used. Its results can be compared with results obtained from Boolean logic and Fuzzy logic based on WLC.