RESEARCH ARTICLE
Sanitary landfill site selection by integrating AHP and FTOPSIS
with GIS: a case study of Memari Municipality, India
Sk Ajim Ali1&Farhana Parvin1&Nadhir Al-Ansari2&Quoc Bao Pham3,4&Ateeque Ahmad1&Meena Sansar Raj5,6& Duong Tran Anh7&Le Huy Ba8&Van Nam Thai9
Received: 25 May 2020 / Accepted: 25 September 2020
# Springer-Verlag GmbH Germany, part of Springer Nature 2020 Abstract
Sanitary landfill is still considered as one of the most significant and least expensive methods of waste disposal. It is essential to consider environmental impacts while selecting a suitable landfill site. Thus, the site selection for sanitary landfill is a complex and time-consuming task needing an assessment of multiple criteria. In the present study, a decision support system (DSS) was prepared for selecting a landfill site in a growing urban region. This study involved two steps of analysis. The first step of analysis involved the application of spatial data to prepare the thematic maps and derive their weight. The second step employed a fuzzy multicriteria decision-making (FMCDM) technique for prioritizing the identified landfill sites. Thus, initially, the analytic hierarchy process (AHP) was used for weighting the selected criteria, while the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) was applied for addressing the uncertainty associated with decision-making and priori-tizing the most suitable site. A case study was conducted in the city of Memari Municipality. The main goal of this study was the initial evaluation and acquisition of landfill candidate sites by utilizing GIS and the following decision criteria: (1) environmental criteria consisting of surface water, groundwater, land elevation, land use land cover, distance from urban residence and buildup, and distance from sensitive places; and (2) socioeconomic criteria including distance from the road, population density, and land value. For preparing the final suitability map, the integration of GIS layers and AHP was used. On output, 7 suitable landfill sites were identified which were further ranked using FTOPSIS based on expert’s views. Finally, candidate site-7 and site-2 were selected as the most suitable for proposing new landfill sites in Memari Municipality. The results from this study showed that the integration of GIS with the MCDM technique can be highly applied for site suitability. The present study will be helpful to local planners and municipal authorities for proposing a planning protocol and suitable sites for sanitary landfill in the near future. Keywords Geographic information system . Analytical hierarchy process . Landfill siting . Fuzzy TOPSIS . Waste management
Introduction
The importance of solid waste management has become more significant than before with an increasing quantity of waste generation due to population growth, urbanization, and chang-es in human lifchang-estyle (Aghajani Mir et al. 2016; Ali 2016). Therefore, an integrated solid waste management plan is es-sential that will cover all necessary steps of waste manage-ment from generation to final disposal for environmanage-mental sus-tainability and better human health (Beskese et al. 2015). Among the different steps involved in the managing of mu-nicipal solid waste (MSW), the final disposal is the most im-portant from the viewpoint of environmental degradation and impacts on public health (Domingo and Nadal2009; Sankoh
2013; Sankoh et al.2013; Sharma et al.2013). Nevertheless, the management of MSW is becoming a significant problem Highlights
• Landfill site selection is a global concern in order to reduce environmental and health issues.
• Multicriteria decision analysis is the best and accepted technique for landfill site selection.
• Fuzzy removes bias and ambiguity from decision criteria and offers the best evaluation result.
• Geographic information system offers accurate spatial analysis for solving a defined problem.
Responsible Editor: Philippe Garrigues
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11356-020-11004-7) contains supplementary material, which is available to authorized users.
* Quoc Bao Pham
phambaoquoc@duytan.edu.vn
Extended author information available on the last page of the article
for municipal authorities, city planners, and decision-makers due to the increasing population, rapid urbanization, inade-quate resources, and financial issues (Ali2016; Hazra and Goel2009). There are more significant problems in develop-ing countries where the unscientific method of solid waste management is practiced due to population growth and the poor state of human consciousness (Hasan2004; Gorsevski et al.2012). These practices are not only accountable for gen-erating an enormous quantity of solid waste but also respon-sible for inappropriate dumping of waste which is now a crit-ical environmental challenge faced by humans (Rahman et al.
2008; Gbanie et al.2013).
Improper methods of waste disposal have negative impacts on groundwater, surface water, air, and soil which also affect public health (Moghaddas and Namaghi2009). Waste dispos-al in unscientific ways have negative impacts on hedispos-alth. Many literatures showed the health impacts on residents living nearer to waste dumping sites and incinerators (Rushton
2003; Minichilli et al.2005). The present situation of waste management, i.e., poor waste disposal method, is the same in all developing countries, with common characteristics like a large quantity of waste generation, untimely collection, open-ly throwing away, burning, dumping, and landfilling in an unscientific manner (Troschinetz and Mihelcic 2009; Guerrero et al. 2013). Thus, environmental consideration should be emphasized on siting sanitary landfills for scientific waste disposal. Recently, many studies have proposed and focused on sanitary landfill (Kara and Doratli2012; Marín et al.2012; Ramjeawon and Beerachee2008) for waste dis-posal because of its minimum infiltration and percolation rate which is a safeguard for ground water pollution. However, it is not an easy task to find the suitable site for landfilling as it requires evaluation of several factors like the availability of land, financial assistance, state and regional guidelines, public awareness, and environmental and health concerns (Kontos et al.2005; Chiueh et al.2008).
Geographic information system (GIS) is a computer-operated system that is very useful for representing the geospatial data for resolving a well-defined problem (Costache et al.2020; Prăvălie and Costache2013; Vahidnia et al.2009). Recently, GIS has been successfully used for suitability analysis for determining the degree of suitability or unsuitability for specific cases. With growing interest in the GIS application, the integration with multicriteria decision-making (MCDM) helps decision-makers to make out practical problems and then find the appropriate solutions (Chen et al.2010). Many researches have applied MCDM techniques and GIS for landfill suitability analysis and landfill site selection (Kara and Doratli2012; Lukasheh et al.2001; Soroudi et al.2018; Unal et al. 2019). Several GIS-based techniques have also been suggested for suitable landfill site selection (Kontos et al.2003; Chiueh et al.2008; Zamorano et al.2008). The suitability analysis for defining landfill sites
is a tremendously challenging task because the selection pro-cess archetypally requires spatial data concerning various sit-ing rules, regulations, factors, and constraints (Ali and Ahmad
2020). However, the accurate result can be found through GIS integration with spatial information (Kontos et al. 2005; Delgado et al. 2008; Sharifi et al. 2009; Nas et al. 2010; Donevska et al. 2011; Gorsevski et al. 2012; Demesouka et al.2013; Khorram et al.2015; Chabuk et al.2017). Thus, a multicriteria decision support system combined with GIS can offer an ideal site selection tool to decision-makers (Chang et al. 2008; Zucca et al. 2008; Aragonés-Beltrán et al.2010).
There are several techniques available for landfill site se-lection, like mathematical modeling, investigative processes, and several multicriteria decision-making approaches includ-ing analytical hierarchy process (AHP), fuzzy analytical hier-archy process (FAHP), the technique for order preference by similarity to ideal solution (TOPSIS), and other techniques that can be combined with GIS. AHP and fuzzy TOPSIS have been effectively used as a site selection technique (Onut and Soner2008; Gorsevski et al.2012; Beskese et al.2015; Guler and Yomralioglu 2017). GIS is a fundamentally geospatial information system that has a different function such as man-aging, storing and modifying, and analyzing large sizes of spatial data from different sources with different scales (Costache2019). It is ultimate for an innovative site selection process that can efficiently repossess, evaluate, and display spatial results according to the coordinates and characteristics of each place (Guiqin et al.2009). Due to such advantages of GIS, it has been extensively used by many scholars in differ-ent countries to achieve the goal of landfill site selection (Demesouka et al. 2014; Hafezi Moghaddas and Namaghi
2011; Khamehchiyan et al. 2011; Kontos et al. 2003; Lukasheh et al. 2001; Özkan et al.2019;Şener et al.2010; Tercan et al.2020; Yesilnacar and Cetin2005; Yildirim2012; Zamorano et al.2008).
AHP is a widely applied decision-making approach to support multiple criteria. Different studies have shown the result of AHP combined with GIS in solving landfill site selection (Allen et al.2003;Şener et al.2006; Wang et al.
2009; Ghobadi et al. 2013; Feizizadeh et al. 2014; Khorsandi et al.2019). The rating and weighting of landfill suitability criteria are usually expressed in the linguistic term, which makes the result biased. Hence, many scholars make an effort to use fuzzy multicriteria techniques like fuzzy TOPSIS in landfill site selection (Beskese et al.
2015; Kharat et al.2016). So, in the present study, the afore-mentioned techniques (i.e., AHP and fuzzy TOPSIS) were applied because of their accepted results in scientific journals. In the case of the study area, the output results offer an innovative contribution that is really necessary in the current situation of waste management where suitable sanitary landfill sites of great urgency are required.
Fuzzy TOPSIS offers a positive and negative ideal solution which minimizes and maximizes the cost and benefit criteria for an ideal solution (Kelemenis et al.2011). It is noted that for site selection of landfills, the final decision has made through fuzzy to interpret the linguistic term to overcome the uncer-tainties with real-world phenomena.
A recent study integrated MCDM with GIS for selecting a landfill site in Naqadeh, Iran, using AHP and TOPSIS (Khorsandi et al.2019). In their study, AHP was used for weighting the selected decision criteria, and afterward, the TOPSIS model was used for identifying and prioritizing the best landfill site among all candidate sites. But the traditional TOPSIS model has many disadvantages like being unable to produce a good correlation between criteria, uncertainty in obtaining weights, and the possibility of an alternative close to the ideal and nadir point (Xu et al.2015). Thus, in the present study, we used the AHP and FTOPSIS model for weighting the landfill selection criteria and selecting the best site, respectively. The main advantage of using the fuzzy tech-nique for order preference by similarity to ideal solution (FTOPSIS) instead of the traditional TOPSIS is to defuzzify the uncertain rating of decision criteria (Wang and Elhag
2006). Moreover, rating criteria using linguistic variables suf-fer from the issue of spatial unit aggregation which results in the loss of information phenomenon. However, this ambiguity is better addressed using fuzzy numbers instead of crisp scores under the assumption that this is a good solution that decision-makers can provide. Additionally, the fuzzification of the rat-ing approach provides a way to handle decision-makers’ un-certainty regarding the boundaries of their preferences.
As a growing urban city, the municipal, commercial, and hospital wastes in Memari Municipality have been unscientif-ically disposed beside the Damodar River located in the south-ern part of the city, which could lead to various environmental and health problems. Thus, it is urgent to conduct an engineered plan and model for suitable landfill site selection by considering both environmental and economic factors. The present study aimed to identify suitable sites for landfill in Memari Municipality using MCDM techniques and GIS.
Materials and methods
Case study area
Memari Municipality is located in the southeastern part of the Bardhamman District of West Bengal, India (Fig.1). It is a fast-growing urban census town that has experienced signifi-cant population growth since the last decades. Memari Municipality with an area of 14.68 km2has about 41,000 population and 9638 households with an average live ratio of 4 persons per family. This densely populated urban area (4533 persons/km2) consists of 16 municipal wards out of
which Ward No. 1 is the most populous and Ward No. 6 is the least populous with a population of 4433 and 1613, re-spectively. On the other hand, Ward Nos. 7, 8, 11, 12, and 16 are mainly congested with market places, offices, schools, and other built environments. The literacy rate in the study area is about 85% and the sex ratio is 978 females per 1000 males which is a good indication of a better life and human welfare. The population of the city has increased by 15% over the last 10 years. The demographic profile of the study area indicates that it is growing and becomes more populated in the future.
The subdistrict headquarter ‘Purba Bardhaman’ is about 29 km and the state headquarter‘Kolkata’ is about 88 km from the study area. The average elevation is 25 m from the mean sea level. Hot summer and cold winter are the main charac-teristic features of the climate in the study area. The average annual rainfall is about 1255 mm with the highest rainfall during July and August. The maximum temperature reaches above 40 °C during hot summer, whereas the temperature goes down below 12 °C during December and January.
As the main goal of this study was to identify suitable sanitary landfill sites in the study area, it is crucial to empha-size the pattern of waste generation and treatment or manage-ment systems throughout the city. Currently, the city has been generating about 16,315 kg (16.315 MT) waste per day. The average per capita waste generation rate is 0.3935 kg. There is no proper arrangement of waste storage bins and secondary points of collection. Generally, wastes are dumped openly beside roads and collected manually in a tractor for transporting and openly disposing beside the Damodar River. No proper methods of segregation and disposal are being practiced here. As a result, direct contamination with soil and water is the major environmental threat that was no-ticed. The situation with waste generation and treatment is becoming worse day by day. From a personal interview with the municipal authorities, it was known that they are planning for a sanitary landfill site and searching for a suitable land by considering environmental and economic factors. Thus, it is necessary to carry out a study that can put forward a suitable landfill site for managing generated waste in the coming days.
Modeling approach
The detailed hierarchical structure of the decision process for the modeling approach in landfill site selection is illustrated in Fig. 2. The study consists of three stages, i.e., setting the objective and selection of decision criteria, creation of the GIS database and identification of suitable candidate sites, and finally, utilization of fuzzy multicriteria decision-making to identify the most suitable site. The first stage defines the key objective of the decision hierarchy for selecting the most suit-able site. The second stage represents the multicriteria consid-eration by taking environmental and economic factors. Several studies used environmental considerations in landfill
Fig. 1 Location of the study area: a map of India showing the location of Memari Municipality, b ward division of Memari Municipality, and c existing physical features inside the Memari Municipality
site selection to reduce the contamination risk and potential health problems associated with proximity to the landfill source, while the economic consideration reduces the land value, transportation cost, and operational cost (Chang et al.
2008; Guiqin et al.2009; Kontos et al.2003; Mănoiu et al. 2013). By keeping these considerations, suitable landfill sites were selected but the most suitable site was determined in the third stage using FTOPSIS. The study was carried out in the year 2019; problem identification, approval from municipal authorities, personal interview, and discussion with present issues were done during January to May 2019, while method-ology development, gathering of experts’ views, field survey, and map preparation were done during June to December 2019.
For the GIS layer, the database of rivers, ponds, tube well, water pipeline, land elevation (DEMs), land use, dis-tance from urban residence and buildup, and sensitive places as environmental factors and distance from the main road, metaled road, population density, and land value as e c o n o m i c f a c t o r s w e r e c o n s i d e r e d f o r M e m a r i Municipality and collected from different sources like the Office of Municipal Corporation (OMC), West Bengal; District Statistical Handbook (DSH); Landsat-8 images of the US Geological Survey (USGS); SAS.Planet; and Google Earth. The details of the GIS database are summa-rized in Table1. All geographical features were imported in a GIS environment with the same projection system (UTM-45N) and equal cell size (10 m). For instance, to obtain the GIS database of the rivers, the line features of rivers were imported to show the specific distance to the river. This distance map was then classified with suitable and unsuitable scores and converted into a raster map. The raster layer was then reclassified, and the same procedure was repeated with each selected criterion for weighted overlay.
Landfill site selection factors and evaluation criteria
The selection of a suitable landfill site requires evaluation of extensive environmental as well as socioeconomic criteria to evade succeeding trouble and long-term effects on environ-mental component like contamination of groundwater, surface water, and soil (Gorsevski et al.2012; Gbanie et al.2013). It is not always essential that the same criteria would be important in all study regions; instead, the significance of criteria differs with changing geographical location. As far as the present study is concerned, the landfill site suitability criteria were well-thought-out by the observance of local environmental and economic factors, and spatial suitability scores were con-sidered by following the detailed literature survey and guide-lines of the Pollution Control Board, Government of India, on landfill site selection specification. The present study assessed twelve decision criteria, out of which eight criteria were taken from an environmental point of view where far distance was considered as the most suitable and four criteria from an eco-nomic point of view where closer distance and lower value were taken as the most suitable for sanitary landfill.
A hierarchical decision-making procedure in the GIS envi-ronment was prepared for landfill site selection which is illus-trated in Fig.2. It reveals that the landfill site selection process was completed in three stages. The second stage was the use of GIS-based AHP to identify suitable landfill candidate sites. The information required for preparing the map of each se-lected criterion, subcriteria, and alternatives of each layer of this study is shown in Table 2. According to this table, the scores between 1 and 9 were assigned to the alternatives of each subcriterion, where 1 and 9 indicate unsuitable and high-ly suitable classes, respectivehigh-ly. The third stage used FTOPSIS to prioritize the candidate sites. These two stages bear out the first stage to identify the most suitable sanitary landfill site in the study area.
Table 1 GIS database used in the
present study Data Date source Map scale
Rivers Google Earth search engine 1:40,000
Ponds and other water bodies Google Earth search engine 1:40,000 Tube well Municipal authority, Govt. of West Bengal, India 1:30,000 Water pipeline Municipal authority, Govt. of West Bengal, India 1:30,000 Land elevation ALOS World 3D global digital surface model (GDSM) 1:40,000
Land use land cover SAS.Planet 1:40,000
Urban resident and buildup Municipal authority, Govt. of West Bengal, India 1:40,000 Sensitive place Municipal authority, Govt. of West Bengal, India 1:40,000 State high way Google Earth search engine 1:30,000 Urban metalled roads Google Earth search engine 1:30,000 Population density Municipal authority, Govt. of West Bengal, India 1:40,000
Table 2 Landfill site suitability criteria, subcriteria, alternatives, scores, and their weight using analytic hierarchy process (AHP)
Criteria Subcriteria Alternative Score Weight
Environmental Distance from river and canal (m) < 200 1 0.0253
200–400 3
400–600 4
600–800 6
> 800 9
Distance from waterbodies (m) < 200 1 0.0158
200–400 2
400–600 4
600–800 7
> 800 9
Distance from tube well (m) < 100 1 0.0298
100–200 3
200–300 5
300–400 7
> 400 9
Distance from pipeline (m) < 100 1 0.0326
100–200 3 200–300 4 300–400 6 > 400 9 Land elevation (m) 10 to 19 1 0.0454 19 to 22 3 22 to 25 7 25 to 28 9 28 to 46 5
Land use land cover Waterbodies 2 0.0616
Sessional agriculture 7
Builtup area 1
Vegetation 3
Vacant land 9
Distance from residential area (m) < 200 1 0.1013
200–400 3
400–600 5
600–800 7
> 800 9
Distance from sensitive place and restricted places (m) < 100 1 0.0652 100–200 3 200–300 5 300–400 7 > 400 9
Socioeconomic Distance from state highway (m) < 200 9 0.1006
200–400 7
400–600 5
600–800 3
> 800 1
Distance from urban metalled roads (m) < 200 9 0.1211 200–400 6 400–600 4 600–800 3 > 800 1 1756–2785 9 0.1643
Environmental criteria
Surface water Landfill could be long-term threat to both sur-face and groundwater (Gorsevski et al.2012). Therefore, land-fill sites should be located at a specific distance from surface water like lakes, rivers, and ponds (Paul2012). According to India MSW rules 2016, a minimum 200 m distance should be kept up around surface water. Literature has proved that land-fills should not be found in or adjacent to surface water and keep definite distances to reduce surface water pollution from waste contaminants. Several studies used a certain distance for landfill site suitability modeling, for instance, 100 to 300 m interval for surface water like lakes, ponds (Chang et al.2008; Gorsevski et al. 2012; Ebistu and Minale 2013), rivers (Gemitzi et al.2006; Akbari et al.2008; Ebistu and Minale
2013; Gorsevski et al.2012), and canals (Jaybhaye et al.
2014).
Different buffer distances were measured to the surface water location. In the present study, the surface water bodies like rivers and ponds are mainly confined in the central part, and their availabilities are less in the outlying part (Fig.3aand
b). The higher distance from the water bodies indicates higher suitability for considering suitable landfill sites.
Groundwater Groundwater is the main source of drinking water. The contamination of groundwater would be a great threat to the environment and public health. The pollutants from landfill leaching and infiltrating are one of the major environmental and health concerns (Domingo and Nadal
2009; Sankoh 2013). Therefore, looking toward long-term safety, distinct distances should be kept from ground-water sources. The present study collected coordinates of the tube well and water supply pipeline to measure the distance from these features to put a suitability rank. Initially, the point and line feature for the tube well and the water pipeline were digitized and buffer distance was measured. Figure3c and dare the suitability score map of the tube well and pipeline based on groundwater suscepti-bility consideration.
Land elevation Land elevation is a substantial factor for uncovering suitable landfill sites because it is the main deter-mining factor of environmental attributes like slope, aspect, and curvature which maintain an important role in the earth and atmospheric process (Gallant and Wilson 2000; Gruber and Peckham2008). Land elevation has opposite kith and kin with landfill suitability, and it means that consideration of the suitability of an area for a landfill site would be decreased with increasing elevation of land (Kontos et al. 2005). A steep slope has a high risk of contamination and leachate flow and should not be considered as suitable for waste landfilling (Ebistu and Minale 2013). Elevation is not only important from an environmental point of view but also from an eco-nomic consideration because of lower elevation, and a flat surface has low excavation costs (Wang et al.2009). So, for considering suitable landfill sites, lower elevation or flat sur-faces are better preferred than the higher surface. Land eleva-tion was calculated using ALOS World 3D global digital sur-face model (GDSM) with a 30-m spatial resolution (https://
www.eorc.jaxa.jp/ALOS/en/aw3d30/index.htm). The
elevation of the study area ranges from 0 to 46 m. A high pixel value shows that the areas are low suitability and a low pixel value shows high suitability (Fig.3e).
Land use land cover Land use land cover is an important land criterion that should be considered for resolving public accep-tance regarding the election of land for landfill sites (Gorsevski et al. 2012). Thus, land cover like water bodies, agricultural field, proximity to resident and buildup, and dense populous areas are not suitable for a landfill site and the pre-ferred distance should be kept for lessening environmental hazards and health problems (Jaybhaye et al. 2014; Guler and Yomralioglu2017). The high-resolution imagery (Bing Table 2 (continued)
Criteria Subcriteria Alternative Score Weight
Population density (persons/km2) 2785–5006 7 5006–7773 5 7773–8938 3 8938–11,050 1
Land value (lakhs/kata) 0.40–1.24 9 0.2362
1.24–1.73 7
1.73–2.34 5
2.34–3.13 3
3.13–4.98 1
Fig. 3 Environmental criteria for landfill site selection: a distance from the river and canal, b distance from waterbodies, c distance from the tube well, d distance from the water pipeline, e land elevation, f land use land cover, g distance from urban resident and buildup area, h distance from sensitive and restricted placesMaps satellite with 1 m spatial resolution from SAS.Planet) was used for land use classification. The signature of land features was collected and supervised classification was used (Fig.3f). The classification result shows that a major portion of the municipality comes under vacant land and agricultural fallow. Only the central portion is concentrated with high buildup and residence. It is a fast-growing urban town, and with an increasing population, the land area is continuously used for construction and new buildup. Therefore, the exact consideration of land features is important, looking toward future planning. In this study, the built-up area and water bodies were assigned with a low suitability score; vegetation, agricultural fallow, and vacant land were assigned with a high suitability score. Here, 1 means the least suitable and 9 means the most suitable for the landfill site.
Distance from urban residence and buildup According to the Municipal Solid, Waste Management rules 2016, India, a san-itary landfill cannot be sited within 500 m of urban residential areas. Therefore, the areas within 500 m were scored as 1 indicating an unsuitable area for waste landfill site and farther areas from urban residences between 3 and 7 indicate the most suitable areas for landfill site (Fig.3g).
Distance from sensitive and restricted places As per the Indian Municipal Solid, Waste Management rules 2016, san-itary landfill sites are not permitted either near sensitive places like children’s parks, natural park, offices, banks, etc. or to critical habitat areas and sensitive eco-fragile areas. Therefore, as a growing urban town, this parameter should be considered because waste landfill sites should not be permitted near re-stricted and sensitive places (Kontos et al.2005; Guler and Yomralioglu2017). It is recommended in the present study that within 100 m of sensitive and restricted places (schools, college, banks, rail station, children’s park, and offices) is considered as unsuitable for landfill sites and a farther distance has to be considered for a suitable landfill site (Fig.3h). Socioeconomic factors
Distance from the state highway and urban metalled roads According to the Waste Management rules 2016, a minimum 200 m buffer should be maintained from roads, railway, and local urban metalled roads. However, a greater distance from the road would increase transport costs. Previous literature consigned a higher suitability score to close distance to a road network from an economic point of view to reduce the trans-port cost (Guiqin et al.2009; Gorsevski et al.2012; Das and Bhattacharyya2015; Guler and Yomralioglu2017). But from an environmental point of view, landfill sites should not be located nearer to the roadside (Akbari et al.2008; Babalola and Busu2011). However, in the present study, both econom-ic and environmental considerations were taken and buffer
distance was measured from the state highway and local metalled roads. For the study area, closer to local roads was given lower scores because the location of this road in the study area is within urban residences which should have lower suitability scores (Fig.4aandb).
Population density Population is an important parameter to define highly built-up and residential areas because high population density is always found in highly accessible areas. Areas with a high density of population are an indi-cation of a high availability of better amenities and land-fills should be avoided from those areas. Many research findings have revealed that public opposition increases for siting landfill nearer to highly residential areas, and the suitability score of landfill site decreases with increas-i n g p u b l increas-i c o b j e c t increas-i o n ( L o b e r 1 9 9 5; M a h i n i a n d Gholamafard 2006). Hence, a waste landfill site should not be placed nearer to densely populated urban areas (Babalola and Busu 2011; Donevska et al. 2011; Demesouka et al. 2013). The population density map of the study area was prepared using the Choropleth tech-nique to show the areal differentiation of population living per square kilometer area (Fig.4c). This thematic map was first converted into a raster layer and then reclassified ac-cording to suitability score.
Land value The price of land is a factor that should be consid-ered as a cost criterion. The high land value increases the construction cost of the sanitary landfill sites. The land value in the study area ranges between 0.80 and 7 lakhs per kata (1 kata = 0.00668 ha). A GPS-based survey was conducted throughout the study area to know the actual land prices on different places, and x, y coordinates were collected for spatial mapping. Figure4dshows that land prices in the center of the city are quite high than the periphery part of the growing urban area. Land price is very much important for the study area because financial assistance is a great concern for Memari Municipality. So, for a suitable landfill site, the periphery of the urban center has high priority.
Calculating the criteria weight by AHP
AHP is an important multicriteria decision-making ap-proach. The AHP was given and developed by Saaty in 1977, that is why it is also called as Saaty’s method of decision-making (Saaty1980; Saaty and Vargas2000). It is an easy and flexible technique that helps the decision-maker to set the weight of the decision criteria and offers a synthesized result (Saaty1990a). The most inventive task in AHP is to select significant factors for decision-making, and all factors should be arranged in a hierarchical struc-ture (Saaty 1990b; Saaty2012). From a pragmatic view, AHP consists of several sequential steps together with
preparation of the pairwise comparison matrix, assigning rank, deriving criteria weight, and developing overall pri-orities for making the final decision (Mu and Rojas2017). It is a popular technique for weighting the selected deci-sion criteria and to determine the most important criteria among them. The main steps involved in AHP have been referred to in many studies (Saaty and Vargas 2000; Chamodrakas et al.2010; Raut et al. 2011; Kharat et al.
2016; Ali and Ahmad 2018). The steps below were followed in the present study.
1. First of all, the goal was defined to identify the most suitable landfill candidate sites.
2. Then the structure of hierarchy was established, which was constituted by the selected criteria to reach the goal. In the present study, there are 12 decision subcriteria, which are divided into environmental criteria (EN-1 to EN-8) and economic criteria (EC-1 to EC-4).
3. Finally, a pairwise comparison matrix (PCM) of the se-lected criteria was established by ranking scale to give the relative importance to the criteria in the decision-making process.
Saaty developed the fundamental scale of pairwise com-parison to put relative importance in place of the criteria that
works in a reciprocal function (Saaty1980), for example, the pairwise comparison matrix P, in which the criteria cijof the matrix is the relative importance of the ithfactor with respect to the jthfactor and would be the reciprocal ijthfactor. This was calculated using Eq. (1):
P ¼ cij ¼ 1 c12 c13 ⋯ ⋯ c1n 1=c12 1 ⋯ ⋯ ⋯ c2n 1=c13 ⋮ 1=c1n ⋯ ⋯ ⋯ 1 ⋯ ⋯ c3n ⋯ ⋯ ⋯ 1 2 6 6 6 6 6 4 3 7 7 7 7 7 5 ð1Þ
4. The expert’s view is required to judge and develop the set of the pairwise matrix. In this study, six experts (two municipal engineers, two municipal workers engaged with waste transportation, and two academicians who have good knowledge about landfill site suitability) were involved to fill the blank matrix containing the criteria. The reciprocals automatically share out to each criterion in the pairwise matrix as shown in Eq. (1).
5. The normalized column sum (NCS) of all eigenvectors was calculated for deriving the weight of the selected criteria in the next hierarchical level.
6. By calculating all requirements of the pairwise compari-son matrix, the consistency of the matrix needs to be
Fig. 4 Evaluation criteria of landfill site selection for economic concern: a distance from the state highway, b distance from urban metalled roads, c population density, d land value
identified using the eigenvalue. To compute the consis-tency index (CI), the largest eigenvalue (λmaxX) was con-sidered. It was computed using Eq. (2):
λmaxX ¼ ∑nj¼1cijWj
Wi ð2Þ
whereλmaxX is the largest eigenvalue of the pairwise ma-trix, and Wi and Wj are the weights of ith and jthfactors, respectively.
7. The preparation of the pairwise comparison matrix and calculating the criteria weight is not enough and satisfac-tory for the decision-making process. The true judgment of the decision-making process depends on the consisten-cy measure. It is suggested that if the consistenconsisten-cy ratio (CR) of the decision matrix would be > 0.1, it will be considered as inconsistency and the decision matrix should be repeated with proper expert’s view. To evaluate the consistency of the matrix, the CI and CR are expressed as Eqs. (3) and (4):
CI¼λmax−n
n−1 ð3Þ
CR¼CI
RI ð4Þ
where n is the size of the matrix and RI is the random index adopted from Saaty (1980) which is found in other studies (Ali and Ahmad2018; Ali and Ahmad2019c).
Based on Eq. (2), the weight of each criterion was calcu-lated as shown in Table2. But these weights cannot be used for further application until the consistency is measured. Thus, Eqs. (3) and (4) was used and the consistency of the decision matrix was found < 0.1 as shown in Table5. Now, these weights of the selected criteria were used for weighted overlay and the preparation of the final landfill suitability map. The main reason behind the application of AHP in this study is to derive the weight of selected decision criteria to find suitable candidate sites for sanitary landfills.
Prioritizing the suitable candidate site by FTOPSIS
TOPSIS is the acronym of technique for order preference by similarity to ideal solution. Hwang and Yoon first introduced this concept in 1981 for solving complex multicriteria decision-making problems (Shahba et al.2017). TOPSIS is an MCDM method used for selecting the ideal one from decision criteria based on the farthest distance from the negative ideal solution (NIS) and the shortest distance from the positive ideal solution (PIS) (Wu et al.2009). There are adequate studies related to TOPSIS application (Gamberini et al.2006; Antuchevičiene
et al.2010; Tupenaite et al.2010; Parvin et al.2020). Using TOPSIS, the ideal and nonideal solutions can be identified simultaneously. Like other decision-making methods, TOPSIS is also criticized by uncertain rating and required to use any particular method which can work with uncertain data (Li and Reeves1999). In this regard, fuzzy TOPSIS can be applied which can remove such uncertainty. The underlying principle of the fuzzy technique is to defuzzify the uncertain rating of decision criteria (Wang and Elhag2006).
The fuzzy TOPSIS was used in the present study to avoid the uncertainty of prioritizing the best landfill candidate site. It was proposed by Chen and Hwang (1992). It is based on the concept that the best alternative should have the shortest dis-tance from the fuzzy positive ideal solution (FPIS) and farthest distance from the fuzzy negative ideal solution (NPIS). The positive ideal solution minimizes the cost criteria and maxi-mizes the benefit criteria, while a negative ideal solution max-imizes the cost criteria and minmax-imizes the benefit criteria (Kelemenis et al. 2011). The triangular fuzzy number was used in this study, as suggested by Chen (2000). To establish the fuzzy decision matrix, each decision criterion was set by the linguistic variables ranging from 1 to 9 (1, 1, 3 for very low; 1, 3, 5 for low; 3, 5, 7 for average; 5, 7, 9 for high; and 7, 9, 9 for very high) which is shown in Table3. FTOPSIS can be calculated by the following steps (Chen and Hwang1992; Chen2000; Zarei et al.2016):
1. Establish the normalized fuzzy decision matrix. The fuzzy normalized value (rij) was estimated by using Eqs. (5) and (6): rij¼ aij cj; bij cj; cij cj ; and cj ¼ max cij
for beneficial criteria
ð Þ ð5Þ rij¼ aj cj ;bj bj ;cj aj ; and aj¼ min aij
for cost criteria
ð Þ ð6Þ
where a, b, and c are the lower, middle, and upper fuzzy numbers, respectively. For beneficial criteria, all values are divided by maximum value and for cost criteria; the minimum value is divided by all values.
Table 3 Triangular fuzzy number and their importance
Term used Triangular fuzzy number Very low 1, 1, 3
Low 1, 3, 5 Average 3, 5, 7 High 5, 7, 9 Very high 7, 9, 9
2. Estimate the weighted normalized fuzzy decision matrix. vijis defined in Eq. (7):
vij¼ rij wj ð7Þ
where rijis the normalized fuzzy value, and wjis the fuzzy weight for each respective jthcriterion.
3. Determine the FPIS and FNIS. The FPIS and FNIS were calculated by using Eqs. (8) and (9):
Aþ¼ vþ1; vþ2; vþ3; …………vþn where; vþ j ¼ max vij3 ð8Þ A−¼ v−1; v−2; v−3; …………v−n where; v− j ¼ min vij1 ð9Þ where A+ and A−are the fuzzy positive and negative ideal solutions, respectively. vþ1 ….. vþn belong to the benefit criteria and v−1….. v−nbelong to the cost criteria.
4. Now, calculate the distance between each alternative to the FPIS and FNIS using the vertex method, which was introduced by Chen (2000) to determine the distance be-tween fuzzy numbers. This was calculated by the follow-ing equation (Eq.10):
d xð 0; y0Þ ¼ ffiffiffi 1 3 r a1−a2 ð Þ2þ b 1−b2 ð Þ2þ c 1−c2 ð Þ2 h i ð10Þ
5. The distance between each alternative, dþi and d−i, is de-fined in Eq. (11): dþi ¼ ∑ n j¼1d vij; v þ j ; d− i ¼ ∑ n j¼1d vij; v − j ð11Þ
6. Finally, calculate the closeness coefficient CCþi for the ideal solution to prioritize the preference order and identify the most suitable choice. It was calculated using Eq. (12):
CCþi ¼ d − i d−i þ dþi
ð12Þ
where dþi and d−i are the sum of FPIS and FNIS, respectively. Based on this calculated CCþi value, rank 1 was given to the highest preference order and increasing rank toward lower pref-erence order in determining the most suitable landfill candidate sites.
The rationale of using fuzzy TOPSIS in the present study was to select the best landfill candidate site that was derived through AHP-based GIS overlay analysis. In fuzzy TOPSIS, the environmental factors were considered as beneficial criteria (farthest distances are more preferable) and economic factors as cost criteria (shortest distance and lower value are more preferable).
Results
The present case study showed a landfill site suitability map using GIS and multicriteria technique for Memari Municipality, West Bengal, India. The study was conducted in two stages. Initially, GIS and AHP were employed to map the landfill suit-ability and identify the landfill candidate sites. Then, FTOPSIS was used to prioritize the landfill candidate sites and select the most suitable site. Looking toward the study area, a total of 12 landfill evaluation criteria were selected by taking environmen-tal and economic considerations. The AHP was applied to de-rive the weight of selected criteria based on their significance in comparison to other criteria for determining the suitable landfill sites. The weight of each criterion is summarized in Table4. The results revealed that out of a total of eight environmental subcriteria, distance from residential area and distance from sensitive place and restricted places gained the highest weight of 0.1013 and 0.0652, respectively. Consequently, other envi-ronmental subcriteria like land use land cover, land elevation, and distance from water pipeline have also less or more similar weight in considering suitable landfill sites. On the other hand, out of four economic criteria, the land value showed the highest priority with a weight of 0.2362. It indicates that the suitable landfill site would be constructed in a low land price area. The same consideration was also focused for transportation cost, i.e., distance from the roads.
The criteria weight was used for overlaying the raster layers for calculating the landfill site suitability index (LSSI) and creating a landfill suitability map which gives the illustration of the suitable location of municipal landfill candidate sites throughout the study area. The AHP and GIS integration was performed using weighted summation to aggregate all criteria layers into a single layer order to prepare the final suitability map (Fig.5).
The final suitability map was classified into five discrete classes: very high suitable area, high suitable area, moder-ate suitable area, low suitable area, and unsuitable area for landfill. The very high suitable areas were finally taken into consideration for selecting landfill candidate sites and other classes were left out from the analysis of the next stage as not suitable for sanitary landfills. In making the final deci-sion regarding the best landfill site selection, the FTOPSIS was used. The present study found seven candidate sites. Public acceptance and experts’ views were collected from field survey which was carried out during June to December 2019 for preparing the fuzzy decision matrix with respect to the seven landfill candidate sites. As per fuzzy triangular number, the rank of each landfill candidate site with respect to all landfill evaluation criteria was determined which ranges between 1 and 9, where 1 means very low and 9 means very high importance for selecting the landfill site (Table 5). The fuzzy decision matrix was further normal-ized (Table 6). In order to calculate the maximum and
minimum values of each evaluation subcriterion of landfill site selection, the weighted normalized fuzzy value was estimated (Table7).
Table9shows the FPIS and FNIS. In FTOPSIS, it is be-lieved that the best alternative should have the shortest dis-tance from the FPIS and farthest disdis-tance from the FNIS. Table 4 Pairwise comparison matrix and derived weight of the selected subcriteria
Subcriteria EN-1 EN-2 EN-3 EN-4 EN-5 EN-6 EN-7 EN-8 EC-1 EC-2 EC-3 EC-4 Weight EN-1 1 4 0.33 0.5 0.33 0.25 0.2 0.25 0.2 0.2 0.25 0.2 0.0253 EN-2 0.25 1 0.33 0.25 0.2 0.16 0.16 0.33 0.25 0.2 0.16 0.14 0.0158 EN-3 3 3 1 0.5 0.33 0.25 0.33 0.33 0.2 0.2 0.25 0.16 0.0298 EN-4 2 4 2 1 0.5 0.33 0.2 0.25 0.25 0.2 0.25 0.16 0.0326 EN-5 3 5 3 2 1 0.5 0.33 0.33 0.33 0.25 0.2 0.2 0.0454 EN-6 4 6 4 3 2 1 0.33 0.5 0.5 0.33 0.25 0.2 0.0616 EN-7 5 6 3 5 3 3 1 3 0.5 1 0.33 0.33 0.1013 EN-8 4 3 3 4 3 2 0.33 1 0.33 0.25 0.33 0.2 0.0652 EC-1 5 4 5 4 3 2 2 3 1 0.5 0.33 0.25 0.1006 EC-2 5 5 5 5 4 3 1 4 2 1 0.33 0.33 0.1211 EC-3 4 6 4 4 5 4 3 3 3 3 1 0.33 0.1643 EC-4 5 7 6 6 5 5 3 5 4 3 3 1 0.2362
Consistency ratio (CR) = 0.0826. EN-1 = distance from river and canal, EN-2 = distance from waterbodies, EN-3 = distance from the tube well, EN-4 = distance from pipeline, EN-5 = land elevation, EN-6 = land use land cover, EN-7 = distance from residential area, EN-8 = distance from sensitive place and restricted places, EC-1 = distance from state highway, EC-2 = distance from urban metalled roads, EC-3 = population density, EC-4 = land value
Fig. 5 AHP and GIS integration for calculating landfill site suitability index and identifying landfill candidate sites
Thus, seven suitable landfill candidate sites were identified from the final suitability map which was calculated using AHP. To calculate the closeness coefficient for the best land-fill candidate site, the selected criteria were judged with re-spect to the seven candidate sites based on the experts’ deci-sion taken from field survey carried out during June to December 2019. Here, the environmental factors were taken as beneficial criteria and the economic factors as cost criteria. The result revealed that candidate site-7 has the highest pref-erence rank with CCi+value 0.62, and it is considered as the best sanitary landfill site for the study area. Consequently, site-2 is the next suitable landfill site with CCi+ value 0.58. Site-6 and site-3 are moderately suitable with CCi+ values 0.55 and 0.54, respectively, whereas site-1 and site-5 have CCi+values 0.22 and 0.32, respectively, which are least suit-able for sanitary landfill sites (Tsuit-able8 and Fig.6). A post-analysis investigation was also carried out on each landfill candidate site for ground verification which also proves fuzzy TOPSIS as a significant technique for selecting the best and worst choice of alternatives (Table9).
Discussion
Disposal facility of generated waste is a global issue, especial-ly in developing countries, where the quantity of daiespecial-ly waste generation is high but the daily collection, segregation, proper transportation, and suitable place for waste disposal are lack-ing (Ali and Ahmad2019a). Among the other stages of waste management, waste disposal is more challenging because there are many considerations for environmental as well as public health safety (Ali and Ahmad2019b). Thus, suitable places are essential for siting a scientific waste disposal site. Many researchers have shown their keen interest to resolve such problems throughout the world (Akintorinwa and Okoro
2019; Ali and Ahmad2020; Feyzi et al. 2019; Islam et al.
2018). A recent study found that more than 100 studies have been carried out on landfill site suitability using GIS coupled with different multicriteria decision-making techniques
between the years 2005 and 2019 (Özkan et al. 2019). Hence, the importance of studies on landfill site selection in growing urban regions is evident from this study.
The present study area, Memari Municipality, is a growing urban region where the quantity of waste generation in recent year reaches 16.315 MT/day. There is no specific disposal site in the study area and wastes are being disposed openly beside the river Damodar without segregating which may become a serious threat to local communities. Thus, a study on landfill site suitability is very much relevant for the study area. Looking toward the solution of suitable landfill site selection, GIS integrated with the MCDM technique was applied in this study because many excellent scholars have studied MCDM techniques in this regard; many of them also applied multiobjective in siting suitable landfill locations (Stowers and Palekar1993; Current and Ratick1995). But, more re-cently, GIS is being integrated with different MCDM tech-niques for locating landfill sites to minimize public health risks and ecological hazards by more or less comparable criteria to shape the model and select landfill sites in fast-growing urban cities (Afzali et al. 2014; Ali and Ahmad
2020; Chabuk et al.2019; Ebistu and Minale2013; El Baba et al.2015; Guler and Yomralioglu2017;Şener et al.2010; Soroudi et al.2018).
The present study has been accomplished in two inter-connected stages. The GIS-based AHP method was applied with spatial data for analyzing the problem of weighing different geospatial features for potential training areas for identifying landfill candidate sites, which is not a new tech-nique and many studies used the same up to that time for integrating spatial data and screening potential sites for the selection of a suitable landfill (Banar et al.2007; Chabuk et al.2017; Demesouka et al.2013; Guler and Yomralioglu
2017; Guiqin et al. 2009; Khan and Samadder 2015; Moeinaddini et al. 2010; Şener et al. 2010; Sener et al.
2011). But in the second stage of this study, it differs from the conventional method in which ground truth was assessed with respect to the derived landfill candidate sites, and limited studies were based on it (Beskese et al.2015; Table 5 Fuzzy decision matrix
Beneficial criteria Cost criteria
EN-1 EN-2 EN-3 EN-4 EN-5 EN-6 EN-7 EN-8 EC-1 EC-2 EC-3 EC-4 Site-1 7, 9, 9 3, 5, 7 3, 5, 7 1, 3, 5 1, 3, 5 5, 7, 9 1, 3, 5 3, 5, 7 3, 5, 7 5, 7, 9 3, 5, 7 5, 7, 9 Site-2 3, 5, 7 5, 7, 9 7, 9, 9 5, 7, 9 5, 7, 9 7, 9, 9 5, 7, 9 5, 7, 9 1, 3, 5 1, 3, 5 3, 5, 7 7, 9, 9 Site-3 7, 9, 9 3, 5, 7 1, 3, 5 1, 3, 5 5, 7, 9 5, 7, 9 3, 5, 7 5, 7, 9 1, 3, 5 1, 3, 5 3, 5, 7 1, 3, 5 Site-4 1, 1, 3 7, 9, 9 5, 7, 9 1, 3, 5 7, 9, 9 1, 3, 5 3, 5, 7 1, 3, 5 5, 7, 9 3, 5, 7 3, 5, 7 1, 3, 5 Site-5 5, 7, 9 1, 3, 5 1, 3, 5 1, 1, 1 3, 5, 7 1, 3, 5 1, 3, 5 1, 3, 5 3, 5, 7 5, 7, 9 1, 3, 5 1, 3, 5 Site-6 5, 7, 9 5, 7, 9 3, 5, 7 3, 5, 7 5, 7, 9 1, 1, 3 1, 3, 5 3, 5, 7 5, 7, 9 1, 3, 5 1, 1, 3 3, 5, 7 Site-7 1, 3, 5 5, 7, 9 5, 7, 9 3, 5, 7 5, 7, 9 1, 1, 3 3, 5, 7 3, 5, 7 7, 9, 9 1, 1, 3 1, 1, 3 3, 5, 7
Table 6 Nor m al iz ed fuz zy d ec is io n m at ri x Bene fi cia l cri ter ia Cos t cri ter ia E N -1 EN -2 EN -3 E N -4 E N -5 EN -6 E N -7 E N -8 EC-1 E C -2 EC-3 E C -4 Site-1 0.77, 1, 1 0 .33, 0.56, 0.7 0 .33, 0. 6, 0.7 0 .11, 0.33, 0.5 0 .1, 0 .3, 0 .5 0.6, 0.77, 1 0 .1, 0 .3, 0 .5 0.3, 0.7, 0 0 .1, 0 .2, 0 .3 0.1, 0.1, 0.2 0 .1, 0 .2, 0 .33 0.1 , 0.1, 0.2 Site-2 0.3, 0.6, 0.7 0 .55, 0.78, 1 0 .78, 1, 1 0 .56, 0.78, 1 0 .6, 0 .8, 1 0.8, 1, 1 0 .6, 0 .8, 1 0.6, 0.8, 1 0 .2, 0 .3, 1 0.2, 0.3, 1 0 .1, 0 .2, 0 .33 0 .1 , 0 .1, 0 .1 Site-3 0.77, 1, 1 0 .33, 0.56, 0.77 0.11, 0. 3, 0.56 0.11, 0.33, 0.55 0.6, 0.8, 1 0 .6, 0 .77, 1 0 .3, 0 .6, 0 .78 0 .6, 0 .8, 1 0.2, 0.3, 1 0 .2, 0 .3, 1 0.1, 0.2, 0.33 0. 2 , 0.3, 1 Site-4 0.11, 0.1, 0.33 0.77, 1, 1 0 .56, 0.8, 1 0 .11, 0. 33, 0.55 0.8, 1, 1 0 .1, 0 .33, 0.6 0 .3, 0 .6, 0 .78 0 .1, 0 .3, 0 .6 0.1, 0.1, 0.2 0 .1, 0 .2, 0 .3 0.1, 0.2, 0.33 0.2 , 0.3, 1 Site-5 0.55, 0.8, 1 0 .11, 0.33, 0.55 0.11, 0.3, 0.56 0.11, 0.11, 0.33 0.3, 0.6, 0.78 0.1, 0.33, 0.6 0 .1 , 0 .3, 0 .56 0 .1, 0 .3, 0 .6 0.1, 0.2, 0.3 0 .1, 0 .1, 0 .2 0 .2, 0 .3, 1 0.2 , 0.3, 1 Site-6 0.55, 0.8, 1 0 .55, 0.78, 1 0 .33, 0. 6, 0.78 0.33, 0.56, 0.77 0.6, 0.8, 1 0 .11, 0.11, 0.3 0 .1, 0 .3 , 0 .56 0 .3, 0 .6, 0 .8 0.1, 0.1, 0.2 0 .2, 0 .3, 1 0.3, 1, 1 0 .1 , 0 .2, 0 .3 Site-7 0.11, 0.3, 0.56 0.55, 0.78, 1 0 .56, 0.8, 1 0 .33, 0.56, 0.77 0.6, 0.8, 1 0 .1, 0 .11, 0.3 0 .3, 0 .6 , 0 .78 0 .3, 0 .6, 0 .8 0.1, 0.1, 0.1 0 .3, 1 , 1 0.3, 1, 1 0 .1 , 0.2, 0.3 Table 7 Weig hted nor ma liz ed fuz zy d ec ision m at rix Be nef ici al cr it eri a Cos t cri ter ia EN -1 E N -2 E N -3 EN -4 EN -5 EN -6 E N -7 E N -8 EC-1 EC-2 E C -3 EC-4 Site-1 0.77, 1, 3 0 .33, 0.56, 2.3 1 , 2 .8, 5 .44 0 .56, 2.33, 5 0 .8, 3 , 5 0.6, 0.7 7 , 3 0.1, 1, 2 .78 0.3 , 2.1, 3.9 0 .1, 0 .2, 1 0 .3, 0.7, 1.4 0 .7, 1 .4, 3 0.8, 1.3 , 1.8 Site-2 0.33, 0.6, 2 .33 0.55, 0.78, 3 2 .33 , 5, 7 2 .78, 5.44, 9 3 .9, 7 , 9 0.8, 1, 3 0 .6, 2 .3, 5 0.6 , 2.3, 5 0 .2, 0 .3, 3 0 .6, 1.7, 7 0 .7, 1 .4, 3 0.8, 1, 1.3 Site-3 0.77, 1, 3 0 .33, 0.5, 2.33 0.33 , 1 .7, 3 .89 0 .56, 2.33, 5 3 .9, 7 , 9 0.6, 0. 7 7 , 3 0.3, 1.7, 3.89 0.6 , 2.3, 5 0 .2, 0 .3, 3 0 .6, 1.7, 7 0 .7, 1 .4, 3 1.4, 3, 9 Site-4 0.11, 0.1, 1 0 .77, 1, 3 1 .67 , 3.9, 7 0 .56, 2.33, 5 5 .4, 9 , 9 0.1, 0.3 3 , 1 .7 0.3, 1.7, 3.89 0.1 , 1, 2.8 0 .1, 0 .1, 0 .6 0 .4, 1, 2.3 0 .7, 1 .4, 3 1.4, 3, 9 Site-5 0.55, 0.8, 3 0 .11, 0.3, 1.66 0.33 , 1 .7, 3 .89 0 .56, 0.78, 3 2 .3, 5 , 7 0.1, 0.3 3 , 1 .7 0.1, 1, 2 .78 0.1 , 1, 2.8 0 .1, 0 .2, 1 0 .3, 0.7, 1.4 1 , 2 .3, 9 1.4, 3, 9 Site-6 0.55, 0.8, 3 0 .55, 0.78, 3 1 , 2 .8, 5 .44 1 .67, 3.8, 7 3 .9, 7 , 9 0.1, 0.1 1 , 1 0.1, 1, 2 .78 0.3 , 1.7, 3.9 0 .1, 0 .1, 0 .6 0 .6, 1.7, 7 1 .7, 7 , 9 1, 1.8, 3 Site-7 0.11, 0.3, 1 .67 0.55, 0.78, 3 1 .67 , 3.9, 7 1 .67, 3.89, 7 3 .9, 7 , 9 0.1, 0.1 11, 1 0 .3, 1 .7, 3 .89 0 .3 , 1 .7, 3 .9 0.1, 0.1, 0.4 1 , 5 , 7 1.7, 7, 9 1 , 1 .8, 3 A * 0.77, 1, 3 0 .77, 1, 3 2 .33 , 5, 7 2 .78, 5.44, 9 5 .4, 9 , 9 0.8, 1, 3 0 .6, 2 .3, 5 0.6 , 2.3, 5 0 .2, 0 .3, 3 1 , 5, 7 1 .7, 7 , 9 1.4, 3, 9 A − 0.11, 0.1, 1 0 .11, 0.33, 1.66 0.33 , 1 .7, 3 .89 0 .56, 0.78, 3 0 .8, 3 , 5 0.1, 0.1 1 , 1 0.1, 1, 2 .78 0.1 , 1, 2.8 0 .1, 0 .1, 0 .4 0 .3, 0.7, 1.4 0 .7, 1 .4, 3 0.8, 1, 1.3 A * = m ax imum va lue among all in a res p ect ive class ,A − = m inimu m value among all in a respective class
Chang et al.2008; Khorsandi et al.2019). This study has computed closeness value to identify the best and suitable landfill site using decision weight given by decision-makers with respect to a particular criterion in the selection of a san-itary landfill site. In order to make a comparative analysis, different keywords were considered to search literature and a detailed comparison on methodologies applied in this study and in previous studies was made (Table10).
It is obvious that MCDM is not a novel approach and a number of previous studies used the different methods of the MCDM approach in landfill site suitability analysis (Demesouka et al. 2014; Goulart Coelho et al. 2016; Özkan et al.2019). But MCDM is the best option for land-fill site selection because multifactors are considered (like ground water, surface water, residential areas, roads,
sensitive places, etc.) instead of selecting any single criteria (Ali and Ahmad2020).
The studies of Banar et al. (2007), Yousefi et al. (2018), Soroudi et al. (2018), and Tercan et al. (2020) applied a single multicriteria decision-making technique like AHP and decision-making trial and evaluation decision-making trial and evaluation (DEMATEL)-analytical network process (ANP) approach-based weighted overlay to derive suitable landfill sites. However, in these studies, the most important part, i.e., post-analysis investigations, was missing, which should be considered as GIS-based overlay may offer some landfill candidate sites that may not fulfill all the siting criteria. A recent comprehensive study on landfill site selection found only 6 suitable sites out of a total of 49 landfill candidate sites after ground verification (Ali and Ahmad2020). Thus, post-Table 9 Identification of best
landfill sites based on expert’s decisions and post-analysis filed visit
Landfill candidate sites
Experts’ decision for locating landfill site
Reasons identified behind suitability or unsuitability
Site-1 Unsuitable Located on seasonal agricultural lands which are not desirable from an environmental point of view and land owners do not agree to give their sessional agricultural lands for sanitary landfill
Site-2 Permissible Fulfill all criteria including low land price and far distance from selected factors, but presently, there is no road connection and there is a need for a new road construction first and
transportation cost will also be high at that location Site-3 Not suitable Similar causes like site-2
Site-4 Unsuitable Fulfill other criteria but located at a far distance from residential areas which needs high transportation cost
Site-5 Unsuitable Located in the transaction between the vacant place and agricultural lands, fulfill other criteria of landfill site selection but presently there is no road connection between suitable site-5 and waste collection sources
Site-6 Can be considered Having specific distance from selected environmental factors, also close to roads, but nearer to built-up and residential areas Site-7 Highly suitable Desirable distance from selected environmental factors, low land
price and not too far from road which are helpful for least transport cost in waste transportation from collection sources
Table 8 Weighted normalized fuzzy decision for identifying most suitable landfill site
Site dþi d−i CCþi Rank Remarks
Site-1 25.0 7.20 0.22 7 Not suitable
Site-2 16.0 23.0 0.58 2 Suitable
Site-3 16.0 18.4 0.54 4 Considerable
Site-4 18.0 14.3 0.43 5 Not suitable
Site-5 24.0 11.0 0.31 6 Not suitable
Site-6 16.0 19.7 0.55 3 Moderately
suitable
Site-7 13.0 21.5 0.62 1 Highly suitable
analysis verification is essential for accurate result which was carried out in the present study by considering field investiga-tion and taking experts’ decision for siting landfill on that
location (Table9). In this regard, fuzzy TOPSIS was used to identify the best landfill candidate site among all sites derived through AHP.
Fig. 6 Sanitary landfill site selection using the FTOPSIS model
Table 10 Comparison of methodological application in the present study and with other studies Previous studies The present study
Studied by Year Application of AHP Application of fuzzy TOPSIS Post-analysis investigation by fuzzy TOPSIS or other MCDM technique or any other method
Donevska et al. 2011 No (used fuzzy set theory and AHP) No
Gorsevski et al. 2012 Yes No No
Demesouka et al. 2013 Yes No (used TOPSIS) No
Alexakis and Sarris 2014 Yes No No
El-Monsef 2015 Yes No No
Eskandari et al. 2016 Yes No No
Chabuk et al. 2017 Yes No No
Reisi et al. 2018 Yes No No
Khorsandi et al. 2019 Yes No (used TOPSIS) Yes Unal et al. 2019 No (used fuzzy logic) No (used SWOT) No
Chabuk et al. 2019 No (used AHP and RSW) No Yes (used change detection method for comparing the final maps)
Tercan et al. 2020 Yes No No
Ali and Ahmad 2020 No (used fuzzy AHP) No Yes (using direct field visit at derived landfill candidate sites)
Conclusion
The present study is an application of geographic information system and multicriteria decision-making for evaluating the suitable and potential landfill sites for municipal solid waste disposal in Memari Municipality, West Bengal, India. Proper location of the landfill site, availability of management re-sources, and waste treatment are now major challenges to the Memari Municipality with increasing population and gen-eration of municipal solid waste. Thus, a decision-making process is required in order to reach the higher level of problem-solving in urban planning and local area develop-ment. The present study has offered an application of the AHP and fuzzy TOPSIS aggregation procedure for making a decision regarding the selection of a suitable landfill site.
The decision support system was based on GIS and fuzzy TOPSIS, and it was found that site-7 located far from surface water, groundwater, habitation, and urban buildup; located in a vacant land; and where land price is low and nearer to state highway (distance > 500 m, that fulfill the MSWM rules 2016, India) is the most suitable site for landfill based on the present analysis. The result was validated through field survey after GIS-based analysis and then fuzzy TOPSIS was employed. After field survey and site suitability analysis, it was acclaimed that if site-7 and site-2 (the next most suitable land-fill site) could be considered as the two new landland-fill sites at the peripheral part of the urban area, the waste management effi-ciency would be highly effective and practical with minimum transport cost. Therefore, the present study has proposed two new landfill sites (site-7 at the southeast fringe and site-2 at the northern portion of the city) with the required land size, in-stead of selecting a single large landfill site because with the two alternative landfill sites, it will decrease the transport cost and concomitantly increase the waste collection, carriage, number of trips, and disposal facility. Last but not least, it may also be concluded that the proper strategies and allocation of landfill sites by considering environmental and economic factors are essential to managing day by day increasing rates of waste, especially in developing countries where environ-mental issues have been arising due to poor MSW manage-ment. In this regard, the present study would be a source of research in the other part of the growing urban city.
Acknowledgments The authors are highly thankful to the municipal au-thorities for providing information, maps, relevant data, and sharing is-sues regarding new landfill site selection in the study area. We also ac-knowledge four anonymous reviewers, the managing editor, and the editor-in-chief for their valuable time, productive comments, and sugges-tions during the review which helped in improving the overall quality of the manuscript.
Author contributions SAA and FP prepared the data, developed the methodology, analyzed the data, and wrote the original draft regarding the sanitary landfill site selection. NA, QBP, AA, and MSR analyzed the data and critically reviewed the manuscript. DTA, LHB, and VNT
revised the manuscript. QBP is the supervisor for the project. All authors read and approved the final manuscript.
Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Compliance with ethical standards
Ethical approval The present study ensures that the objectivity and transparency are followed in this research along with acknowledged prin-ciples of ethical and professional behavior.
Competing interests The authors declare that they have no conflict of interest.
Research involving human participants and/or animals Human partic-ipants or animals were not engaged or involved in the present research. Therefore, for this study, compliance with ethical standards is not applicable.
Consent to participate Not applicable Consent to publish Not applicable
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